Category Archives: Pedagogy

Quick Tips: Low to No Prep Classroom Activities

Posted on by
Reply

Student engagement is a critical component of higher education and a frequent topic of interest among instructors.  Actively engaging students in the learning process helps increase motivation, supports collaboration, and deepens understanding of course material. Finding activities that instructors can implement quickly while also proving worthwhile to students can be a challenge. I recently attended a conference with a session titled, “Low to No Prep Classroom Activities.”  Jennifer Merrill, psychology professor from San Mateo County Community College, shared some simple classroom activities that require very little or no preparation ahead of time that I thought were worth sharing:

Music:
Playing music as students enter the classroom creates a shared experience which can encourage social interaction, inspire creative thinking, and lead to positive classroom dynamics. It can be used as an icebreaker, to set a particular mood, or specifically relate to the course in some way. Research shows that music stimulates activity in the brain that is tied to improved focus, attention, and memory.

  • Incorporate music as part of a regular classroom routine to indicate that it’s time to focus on the upcoming lesson.
  • Use it to introduce a new topic or review a current or past topic. Ask students to articulate how they think the music/artist/song relates to the course material and then share with the class.
  • Allow students to suggest/select what type of music they would like to hear.

Academic Speed Dating:
Like traditional speed dating, academic speed dating consists of short, timed conversations with a series of partners around a particular topic.Two lines of college students in a classroom, playing a round of academic speed dating. In this case, students are given a prompt from the instructor, briefly discuss their response with a partner, and then rotate to a new partner when the time is up. Partners face each other in two lines, with one line of students continuously shifting through the other line until they return to their original partner. This can also be done by having students form inner and outer circles, instead of lines. A few of the benefits of academic speed dating include:

  • Sharing and questioning students’ own knowledge while gaining different perspectives on a topic.
  • Enhancing communication skills as students learn to express their ideas quickly and efficiently.
  • Providing a safe space to share ideas as students interact with others, which can lead to a positive classroom climate.

Memory:
The classic “Memory Game” consists of a set of cards with matching pairs of text or images. Cards are shuffled and placed face down; players take turns turning over 2 cards at a time, trying to find matching pairs.  In this version, students take part in creating the cards themselves, using index cards, before playing the game. Memory can be used to reinforce learning and enhance the retention of course material.

Suggested steps for implementation:
1. On the board, the instructor lists 10 terms or concepts related to the course in some way.
2. Students are divided into groups of no more than 5 people. Each student in the group selects 2 terms/concepts from the list.
3. Using index cards, students write the name of the term/concept on one card, and an example of the term/concept on another card (e.g., “supply and demand” and “gasoline prices rising in the summer with more people driving”). Examples could also include images, instead of text.
4. When the groups are finished creating their sets of cards, they exchange their cards with another group and play the game, trying to match as many pairs as they can.

  • Use Memory College students playing a memory game with index cards.to review definitions, formulas, or other test material in a fun, collaborative environment.
  • Enhance cognitive skills, such as concentration, short-term memory, and pattern recognition.
  • Facilitate team building skills as students work in groups to create and play the game.

Pictionary:
In this version of classroom Pictionary, students are divided into groups that are each assigned a particular topic.  Each group is tasked with drawing an image representation of their topic, e.g., “Create images that represent the function of two glial cells assigned to your group.”  Ideally, it works best if drawings are large enough to be displayed College students in a classroom doing a gallery walk.around the classroom, such as on an easel, whiteboard, or large Post-it note paper. When each group is finished with their drawings, all students participate in a gallery walk, offering feedback to the other groups.  Facilitate a small or whole group discussion to reflect on the feedback each group received.

  • Enhance problem solving skills and creativity by asking students to think critically about how to represent information visually.
  • Use Pictionary to get students up and moving around the classroom, which will help keep them actively engaged with course content.
  • Help students develop constructive feedback skills as they participate in the gallery walk part of the activity.

Hawks and Eagles:
This activity is a version of “think-pair-share” that gets students up and moving around the classroom.

Suggested steps for implementation:
1. Students pair with someone nearby and decide who will be the Hawk and who will be the Eagle.
2. Give all students a prompt or topic to discuss and allow them time to think about their response (1-3 minutes).
3. Students share their responses with their paired partner (1-3 minutes).
4. Ask Hawks to raise their hands. Ask the Eagles to get up and go find a different Hawk.
5. Students share their responses with their new partner.
6. Repeat steps 4 and 5, if desired, to allow students to pair with multiple partners.
7. Debrief topic with the whole class.

  • Use Hawks and Eagles as an icebreaker activity for students to introduce and get to know one another.
  • Use this activity as a formative assessment to gauge student comprehension of a particular topic.
  • Expose students to multiple perspectives or viewpoints on a particular topic by having them engage with multiple partners.

IQ Cards:
IQ cards (“Insight/Question Cards”) is an exit ticket activity that acts as a formative assessment strategy. At the end of a class or unit, ask students to write down on an index card any takeaways or new information they have learned. On the other side ofStack of index cards. the card, ask them to write down any remaining questions they have about the lesson or unit. Collect student responses and share their “insights” and “questions” with the class at the next meeting.

  • Gather instant feedback from students and quickly assess their grasp of the material, noting where any changes or adjustments might be needed.
  • Reinforce knowledge by asking students to recall key concepts of the lesson or unit.
  • Use IQ Cards as a self-assessment activity for students to reflect on their own learning.

Do you have any additional low or no prep activities you use in the classroom? Please feel free to share them in the comments. If you have any questions about any of the activities described above or other questions about student engagement, please contact the CTEI – we are here to help!

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation 

References:
Baker, M. (2007). Music moves brain to pay attention, Stanford study finds. Stanford Medicine: News Center. Retrieved August 26, 2024, from https://med.stanford.edu/news/all-news/2007/07/music-moves-brain-to-pay-attention-stanford-study-finds.html

Image source: Jennifer Merrill, Pixabay

The Teaching Fellows Project: Community-based Learning in Baltimore City Schools

Posted on by
Reply

[Guest post by Katharine Noel, Associate Teaching Professor, Writing Seminars, Johns Hopkins University]

As a grad student, I was given three days of teacher training before being thrown into a classroom.  This was a composition class with fifty first-year students.  My pedagogical training – if you can call it that – included how to grade on a curve and how to confront cheating and plagiarism without using the words “cheating” or “plagiarism,” a dodge that would supposedly protect the university from lawsuits.  The focus on school protocols implied that teaching itself would be straightforward.  After all, as grad students, we were working at advanced levels; shouldn’t imparting a simplified version of our subject be easy?

Without any real idea of how to convey my “expertise,” I thought back to my own professors.  I wanted, of course, to emulate the best of them, teachers who’d connected with their students, creating excitement while at the same time expressing warmth and engagement.  And yet I’d learned just as many lessons – possibly more – from the ineffective teaching I’d observed: the professor who was charismatic and funny but seemed more concerned with making the students adore him than helping them engage with the subject.  Or the one who started discussions with questions so long and complicated – filled with backtracking, amendments, and counterarguments – that by the time she was finished, students had no idea what they were meant to discuss. Teachers who seemed dismissive or defensive.  Teachers too rigid to pivot; teachers too lax to have an overarching plan.

The Teaching Fellows and WBS mentors outside of a building in Baltimore.

The Teaching Fellows and WBS mentors on a teaching field trip to Baltimore Youth Arts, a creative entrepreneurship and job training program focusing on young people involved in the justice system

Recently, I’ve been reminded of this early teaching experience.  At Hopkins, I teach in The Writing Seminars department.  In addition to standard creative writing courses, for the last five years I’ve taught a community-based learning class in partnership with the nonprofit organization Writers in Baltimore Schools (WBS), founded by Hopkins alum Patrice Hutton. Thanks to  a grant from CTEI, this past year we expanded the class to become the year-long Teaching Fellows Project.

The Teaching Fellows – twelve undergraduates chosen by application from across KSAS – lead weekly creative writing groups in under-resourced elementary and middle schools across the city. The class they take with me provides training and support, as well as the opportunity to work closely with WBS mentors. We study topics like student-centered pedagogy, educational equity, and the social and political context in which Baltimore schools operate.  Writers in Baltimore Schools provides curriculum for teaching elementary and middle-school writing groups, but near the end of the year, each Hopkins student creates, teaches, and revises an original lesson plan based on the interests and needs of their students.

A guest lecture by Ms. Araba Maze, founder of Storybook Maze, which aims to increase book access in Baltimore’s book deserts

The CUE-2 final report stresses the importance of community-based and applied learning, stating that “we should aspire to transform the college experience from one composed solely of traditional elements – lectures, papers, problem sets, and exams – to one in which these elements sit amid a much broader range of learning activities.”  The Teaching Fellows Project is designed to provide this kind of community-based and applied learning opportunity, connecting academic theory to real-world impact. Students bring what they learn in our classroom to their worksites, and bring what they learn in their worksites back to our classroom. Knowledge gained from meaningful engagement in the community is deepened by the knowledge gained through reading, discussions, and guest lecturers, and vice-versa. At times, it all feels very meta: as I teach students to teach, I also point out the techniques and tactics I’m using as a teacher; as students encounter challenges at their worksites, I adjust my curriculum to address those topics that feel most relevant and vital.

One of the first exercises the Teaching Fellows do, based on my own early groping for models, is to think back to their best teachers and try to isolate what made them so effective. Some of these “teachers” are the ones they had in classrooms; others turn out to be coaches, bosses, ministers, co-workers, or relatives. The next week, we repeat the same exercise by discussing frustrating learning experiences.  The complicated interwoven skills of teaching can be most visible when they work together imperfectly, since excellent teachers achieve a kind of magic that means – as with any magician – their moves can be too deft to make out.

My scant training as a grad student seemed predicated on the idea that teaching could and should be easy. What the WBS mentors and I try to convey in The Teaching Fellows Project is very different: that teaching is often hard, confounding, overwhelming, and awkward – as well as thrilling, meaningful, revealing, and joyous.  It can even – at rare moments – feel nearly effortless.

Katharine Noel
Associate Teaching Professor, Writing Seminars
Johns Hopkins University

Prior to coming to Johns Hopkins, Katharine Noel was the Writer in Residence at Claremont McKenna College (2009 to 2013).  From 2002-2009, she was a Jones Lecturer at Stanford University, where she held Wallace Stegner and Truman Capote fellowships in 2000–2002. Before teaching at Stanford, she worked for two years at Gould Farm, a program in the Berkshire Mountains for adults with mental illnesses, and for four years at an Oakland, California shelter for women and children experiencing homelessness.  At Hopkins, in addition to teaching fiction writing, she directs The Teaching Fellows Project.

Image Source: Writers in Baltimore Schools

Lunch and Learn: Generative AI Uses in the Classroom

Posted on by
Reply

On Tuesday, April 23rd, the Center for Teaching Excellence and Innovation (CTEI) hosted a Lunch and Learn on Generative AI Uses in the Classroom. Faculty panelists included Louis Hyman, Dorothy Ross Professor of Political Economy in History and Professor at the SNF Agora Institute, Jeffrey Gray, Professor of Chemical and Biomolecular Engineering in the Whiting School, and Brian Klaas, Assistant Director for Technology and instructor at the Bloomberg School of Public Health. Caroline Egan, Teaching Academy Program Manager, moderated the discussion.  

Louis Hyman began the presentation by reminding the audience what large language models (LLMs) like ChatGPT can and cannot do. For example, ChatGPT does not “know” anything and is incapable of reasoning. It generates text that it predicts will best answer the prompt it was given, based on how it was trained. In addition to his course work, Hyman mentioned several tasks he uses ChatGPT to assist with, including text summarization, writing complicated Excel formulas, writing and editing drafts, making PowerPoint tables, and turning image files in the right direction.

In Hyman’s course, AI and Data Methods in History, students are introduced to a variety of tools (e.g., Google Sheets, ChatGPT, Python) that help them analyze and think critically about historical data. Hyman described how students used primers from LinkedIn Learning as well as Generative AI prompts to increase their technical skills which enabled them to take a deeper dive into data analysis. For example, while it would have been too complicated for most students to write code on their own, they learned how to prompt ChatGPT to write code for them.  By the end of the semester, students used application programming interface (API) calls to send data to Google, used OpenAI to clean up historical documents and images presented using optical character recognition (OCR), and used ChatGPT and Python to plot and map historical data.Two maps of 1850 New England showing the number of congregational churches and the value of congregational property. Data points plotted by students using AI.

Hyman noted that one of the most challenging parts of the course was convincing students that it was OK to use ChatGPT, that they were not cheating.  Another challenge was that many students lacked basic computer literacy skills, therefore, getting everyone up to speed took some time. There was also not one shared computer structure/platform. The successes of the course include students’ ability to use libraries and APIs to make arguments in their data analysis, apply statistical analysis of the data, and ask historical questions about the results they were seeing in the data.

Jeff Gray continued by describing his Computational Protein Structure Prediction and Design course that he has taught for over 18 years. In this course, students use molecular visualization and prediction tools like PyRosetta, an interactive Python-based interface that allows them to design custom molecular modeling algorithms. Recently, Gray has introduced open-sourced AI tools into the curriculum (AlphaFold and RoseTTAFold), which predict 3D models of protein structures.

Example of protein folding using AlphaFold.

One of the challenges Gray mentioned was the diversity of student academic backgrounds. There were students from engineering, biology, bioinformatics, computer science, and applied math, among others. To accommodate this challenge, Gray used specifications grading, a grading method in which students are graded pass/fail on individual assessments that align directly with learning goals. In Gray’s class, students were presented with a bundle of problem sets categorized at various difficulty levels. Students selected which ones they wanted to complete and had the option of resubmitting them a second time for full credit. Gray is undecided about using this method going forward, noting that half of the students ended up dropping the course when they tried to complete all of the problems instead of just a few, and found the workload too heavy.  Another challenge was how to balance the fundamental depth of the subject matter versus application.  To address this, Gray structured the twice weekly class with a lecture on one day and a hands-on workshop the other day, which seemed to work well.

Brian Klaas teaches a one credit pass/fail course called Using Generative AI to Improve Public Health. The goal of this course is to allow students to explore AI tools, gain a basic understanding of how they work, and then apply them to their academic work and research. In addition to using the tools, students discussed the possible harms in Generative AI, such as confabulations, biases, etc., the impact of these tools in Public Health research, and future concerns such as the impact on the environment and copyright law. Klaas shared his syllabus statement regarding the usage of AI tools in class, something he strongly recommends all faculty share with their students.  

Hands-on assignments included various ways of using Generative AI. In one assignment, students were asked to write a summary of a journal article and then have GenAI write a summary of the same article geared towards different audiences (academics vs. high school students). Students were then asked to analyze the differences between the summaries.Sample instagram post created using AI showing people from different cultures dressed as medical professionals. For another assignment, students were asked to pick from a set of topics and use Generative AI to teach them about the selected topic, noting any confabulations or biases present. They then asked GenAI to create a five-question quiz on the topic and take the quiz. A final assignment was to create an Instagram post on the same topic including a single image and a few sentences explaining the topic to a lay audience. All assignments included a reflection piece which often required peer review.

Lessons learned: Students loved the interdisciplinary approach to the course, confabulations reinforce core data research skills, and learning from each other is key.

The discussion continued with questions from the audience: 

Q: What would you recommend to an instructor who is considering implementing GenAI in the classroom? How do they start thinking about GenAI?
JG: Jupyter notebooks are pretty easy to use. I think students should just give it a try.
LH: I recommend showing students what ”bad” examples look like. The truth is, we can still write better than computers. Use AI to draft papers and then use it as an editing tool – it’s very good as an editing tool. Students can learn a lot from that.
BK : I recommend having students experiment and see where the strengths lie, get an overall awareness of it. Reflect on that process, see what went well, not so well. Feed in an assignment and see what happens. Use a rubric to evaluate the assignment. Put a transcript in and ask it to create a quiz on that information. It can save you some time.

Q for Brian Klaas: What version of GPT were you using?
BK: Any of them – I didn’t prescribe specific tools or versions. We have students all over the world, so they used whatever they had. ChatGPT, Claude, MidJourney, etc. I let the students decide and allowed them to compare differences.

Q for Jeff Gray: Regrading the number of students who dropped, is the aim of the course to have as many students as possible, or a group who is wholly into it?
JG: I don’t know, I’m struggling with this. I want to invite all students but also need to be able to dig into the math and material. It feels like we just scratched the surface. Maybe offering an intersession course to learn the tools before they take this class would be helpful. There is no standard curriculum yet for AI. Where to begin…we’re all over the map as far as what should be included in the curriculum.
LH: I guess it depends on what your goals are. Students are good at “plug and chug,” but bad at asking questions like, “what does this mean?”
BK: We didn’t get to cover everything, either – there is not enough time in a one credit class. There are just so many things to cover.

Q: What advice do you have for faculty who are not computer scientists? Where should we start learning? What should we teach students?
LH: You can ask it to teach you Python, or how to do an API call. It’s amazing at this. I don’t know coding as well as others, but it helps. Just start asking it [GenAI]. Trust it for teaching something like getting Pytorch running on your PC. Encourage students to be curious and just start prompting it.
BK: If you’re not interested in Jupyter notebooks, or some of the more complicated functions, you can use these tools without dealing in data science. It can do other things. It’s about figuring out how to use it to save time, for ideation, for brainstorming.
JG: I have to push back – what if I want to know about what’s going on in Palestine and Israel? I don’t know what I don’t know. How do I know what it’s telling me is correct?
LH: I don’t use it for history – but where is the line of what it’s good and not good at?
BK: I would use it for task lists, areas to explore further, but remember that it has no concept of truth. If you are someone who knows something about the topic, it does get you over the hurdles.
JG: You have to be an expert in the area to rely on it.
LH: Students at the end of my course made so much progress in coding. It depends on what you ask it to do – protein folding is very different than history that already happened.

Q: How can we address concerns with fairness and bias with these tools in teaching?
BK: Give students foundational knowledge about how the tools work. Understand that these are prediction machines that make stuff up. There have been studies done that show how biased they are, with simple prompts. Tell students to experiment – they will learn from this. I suggest working this in as a discussion or some practice for themselves.

Q: Students have learned to ask questions better – would you rather be living now with these tools, or without them?
JG: Students are brainstorming better. They are using more data and more statistics.
BK: AI requires exploration and play to get good responses. It really takes time to learn how to prompt well. You have to keep trying. Culturally, our students are optimized for finding the “right answer;” AI programs us to think that there are multiple answers. There is no one right answer for how to get there.
LH: Using AI is just a different process to get there. It’s different than what we had to do in college. It was hard to use computers because many of us had to play with them to get things to work. Now it all works beautifully with smart phones. Students today aren’t comfortable experimenting. How do we move from memorization to asking questions? It’s very important to me that students have this experience. It’s uncomfortable to be free and questioning, and then go back to the data. How do we reconcile this?

JG: What age is appropriate to introduce AI to kids?
LH: Students don’t read and write as much as they used to. I’m not sure about the balance.
Guest: I work with middle and high school teachers. Middle school is a great time to introduce AI. Middle school kids are already good at taking information in and figuring out what it means. Teachers need time to learn the tools before introducing it to students, including how the tools can be biased, etc.

Q: How can we encourage creative uses of AI?
BK: Ethan Mollick is a good person to follow regarding creative uses of AI in education and what frameworks are out there. To encourage creativity, the more we expose AI to students, the better. They need to play and experiment. We need to teach them to push through and figure things out.
LH: AI enables all of us to do things now that weren’t possible. We need to remember it’s an augment to what we do, not a substitute for our work.

Resources:
Hyman slides
Gray slides
Klaas slides

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation 

Image source: Lunch and Learn logo, Hyman, Gray, and Klaas presentation slides, Unsplash

Lunch and Learn: Active Learning Techniques

Posted on by
Reply

On Tuesday, March 12th, the Center for Teaching Excellence and Innovation (CTEI) hosted a Lunch and Learn on Active Learning Techniques: Advice and Guidance from Experienced Faculty. Faculty panelists included Nate Brown, Senior Lecturer, University Writing Program (KSAS); Robert Leheny, Professor and Department Chair, Department of Physics and Astronomy (KSAS); and Michael Falk, Vice Dean of Undergraduate Education and Professor, Department of Materials Science and Engineering (WSE). Caroline Egan, Teaching Academy Program  Manager, moderated the discussion.

Caroline began the session by asking panelists how they got started with active learning and what they would recommend to those who were thinking about implementing it.

Nate Brown described how he heavily relied on his lecture notes to deliver content to students when he first started teaching. As he’s gained more experience, he’s moved away from using lecture notes and actively involves students in their learning.  Brown structures his classes now in such a way that the students drive the conversation and solve problems collectively, leading to greater retention of information and increased engagement. He makes a point of having students think about “why they are doing what they are doing.”

Robert Leheny recalled how the Provost’s Gateway Sciences Initiative from several years ago provided funding to support the redesign of gateway science courses, such as the Introduction to Physics course, which he teaches. The goal of the Gateway Sciences Initiative was to evolve the pedagogy in large introductory science courses to produce better student outcomes.

The Intro to Physics redesign, which was modeled after similar large lecture style courses at NC State and MIT, moved away from a traditional lecture style to a much more interactive experience. Students are divided into groups and sit at round tables instead of in rows, and they solve problem sets together during class rather than at home. This in-class work is partly enabled by a flipped classroom approach which enables students to review the content before coming to class. Leheny said the department now offers two versions of Introduction to Physics that students can select from: an active learning style and a more traditional auditorium/lecture style.

Michael Falk first started implementing  active learning by using  clickers in a 200-student Introduction to Computer Programming course at the University of Michigan several years ago. Since he’s been at Hopkins, his classes have been smaller, allowing him to approach active learning in different ways. Falk gave an example of how he flipped an upper-level materials science course (which is now also part of the Gateway Computing program) so that students work in an online textbook outside of class and do more collaborative work during class. Another example is a First-Year Seminar class taught by Falk, Turing’s Shadow: Uncovering What’s Hidden in STEM. This discussion-based course covers a range of topics, some of which are sensitive, and students are often afraid to speak up. To address this, Falk created a series of discussion cards to help ease students’ discomfort. The cards provide discussion prompts for students, such as “Clarification: Ask for further explanation about something,” and they also inject some fun elements into the conversation by asking respondents to present their response “in the form of a song,” or “while walking around the room very quickly,” for example. It turns the exercise into a game and helps students to feel more comfortable participating in class.

Caroline continued by asking the panelists what their definition of active learning is and to provide a counter-example of it, which would bring its definition into better relief.

NB:   I think it involves giving students a stake in what we’re doing. For example, helping to define the parameters of a paper we’re going to write. I see the professorial role as one of support, like “air traffic control.” With active learning, students are involved in the creation of their own learning.

RL: The primary component of active learning in physics is peer instruction. Students need to be able to solve problems. We don’t use class time to introduce students to concepts, but instead give students an opportunity to practice solving problems where there are resources to help facilitate these skills. For example, students are divided into groups of three and explain to each other how they would go about solving a problem. The act of explaining the problem to someone else helps to solidify their own understanding. A counter example would be the old way of the instructor speaking from the blackboard, talking uninterrupted for most of the class period.

MF: Active learning is learning by doing. Students are engaging with content in a supportive environment. We are teaching a different group of students at Hopkins now – there are many more first- generation, limited-income, and/or underrepresented students with very different backgrounds. We need to think proactively about leveling the playing field for students. This is evident in the data around class outcomes: classes taught using active learning techniques have lower levels of students failing or dropping out. This is even more true for students in underrepresented groups.

RL: We also see this in Intro to Physics. We have the two versions of the course: one in the auditorium (which may have some active learning elements in it), and one designed specifically as an active learning course. The homework and exams are the same in both courses. The outcomes show that failing grades are much less likely to occur in the active learning course.

MF: I used to think my job as an instructor was to deliver content and material. Now, with active learning, I think my job is to deliver an experience.

Caroline continued by asking panelists for a simple active learning technique that instructors can implement right away.

NB: This may sound crazy – it comes from a writer colleague of mine. I was having students read out loud in class and noticed they were struggling: they didn’t feel comfortable, they were shy, or were experiencing language barriers, etc. I then asked them all to read in chorus (at the same time). No one understood what they were hearing, but it shocked them into it being ok to share. It really helped them get over their nerves.

RL: Think-Pair-Share. This technique works very well in a large lecture environment. We give students a multiple choice question and have everyone vote on the answer. Next, they have to find someone who voted differently and try to convince them to change their answer. We then ask students to vote again. The results are that there are usually more correct answers the second time. You do need good questions for this to be effective.

MF: An idea for STEM classes, figure out a way to shorten your lecture and hand out the problem set at the end of class. Allow students to work on them with each other. Ask students to write down the steps on how they would solve the problem, but not actually solve it. Allow time for a report out at the end. This gives them a chance to support each other while organizing information.

CE: A complimentary Humanities example: In my first-year writing class, I hand out labeled strips of paper to students with our class readings on them and ask them to organize the strips in a way that would help the students use the readings in their papers. Also, I give students writing prompts, break them into groups, and ask them to find out where they would find the answers to the prompts. This helps to get them in the right mindset of locating good sources.

Two other examples of active learning were mentioned by faculty guests. One instructor explained how she has students use Legos to construct the analysis of an argument. They connect more and more Legos to build supportive elements of their argument and take away those that they disagree with. Another instructor mentioned that she has students act out responses in class.

The session continued with questions from the audience for the panelists:

Q: In reference to Think-Pair-Share, have you observed any competitiveness among students or reluctance to participate in these activities?
MF: We tell students it has nothing to do with their grade.
RL: We do the same. We also tell them there is no curve and it is possible for everyone to get an A, which reduces overall competitiveness.
NB: One of the great things about this exercise, where students are engaging with each other, is that they get to hear from peers that are from all over the world. We turn it into a social space where they can feel comfortable sharing.

Q: (From a librarian) I recently had about 30 minutes to work with students in a research class. I received feedback from a student that I didn’t do enough active learning in the class, despite doing a brainstorming exercise with them. What do you do when you need more active learning in such a short amount of time?
RL: Explain to students why you structured the class like you did. It will help if you get their buy-in. Maybe the answer is to announce at the beginning that what you’re doing is in fact active leaning.
MF: Students like playing – it makes for a positive learning experience. Perhaps turn part of it into a game/play. And then explain what and why you’re doing it this way.

Q: Are there any active learning experiences to share when you’re guest lecturing? Do you use the same or different strategies?
MF: It needs to be a different strategy. As a guest, you don’t have the advantage of repetition or control of the environment. Explain to students what you’re doing and do the best you can with the constraints that you’re under.
CE: Be very intentional about your choices. At the end, ask them one thing they will remember from the class. This is a good recall exercise.
NB: As a guest speaker, you already are a bit novel since your presence is different than their regular day. Maybe use a novel activity that they will remember.

Q: Could you each share how you put groups together intentionally instead of having students self-form?
RL: Students are put into groups of three. Groups are engineered this way – we switch a few times during the semester. The students don’t know it, but we add them to groups according to their performance on the midterm. In each group, there is one person that scored at the top, one from the middle, and one from a low level. The top level person gets more practice articulating ideas. The lower level person gets the benefit of working with someone who has command of the material. We also group according to gender: we avoid placing two men and one woman in a group to avoid women being excluded. There is research that supports this.
NB: We also do a lot of group work. Halfway through the semester, I ask students to work with someone they haven’t worked with before. I also ask them to sit next to someone different. It results in a richer peer review experience.
MF: I have students do a self-assessment at the very beginning of the course and use the results of the assessment to group students.

For more information about the active learning topics discussed at the event, please see this  Active Learning For Distribution folder of materials developed by Caroline Egan.

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation 

Image source: Lunch and Learn logo, Unsplash, Pixabay

Preparing to Teach: Lessons from a Gamemaster

Posted on by
Reply

Once upon a time, just before the age of COVID-19, I was asked to teach a course for an undergraduate minor program through JHU’s Center for Leadership Education. I began my journey to teaching my first course by meeting the program director for lunch. After the proposition, it became clear to me that there was sparse content for this new course on data visualization, and it would be up to me to develop and deliver it the following semester. With only a few months to prepare, I quickly realized that my quest to create something from nothing would be full of challenges that might result in a perilous journey, but the bounties were rumored to be plentiful.

When I started to delve into the instructional design of my course including developing content, setting learning goals, and creating a syllabus, I was delighted by the discovery that there are many parallels between designing a course and creating an adventure for Dungeons and Dragons (D&D). D&D is a type of role-playing game where players take on roles of fictional characters and attempt to complete a fantasy adventure designed and delivered by the Dungeon Master (I will use the term “gamemaster” for its broader applicability). In a D&D adventure, the gamemaster introduces the fantasy world to the players and presents challenges for them to overcome by performing actions as their characters.  As a gamemaster, I realized that I had resources that would help me structure the course, plan activities, and engage my students.

Learning Goals vs Plotline

One of the first parallels I found was that the learning goals provided a structure much like plot elements would provide a structure to a D&D adventure. The gamemaster tells stories and sets the stage for the players to interact, and, with the stories, they build on each other to an eventual climactic event. In both cases, you have to sequence the elements in a logical way that builds up to the desired result such as a learning goal or a successful adventure. For instance, one of my learning goals was to have students apply visual design principles to different types of presentations of data. I invested time up front in my course structure to ensure students knew a variety of data visualization types, could identify design principles that work for each, and had practice applying those design techniques. Ensuring your participants are adequately prepared for their true test is important, whether it be acing their final project or slaying an evil dragon.

Activities vs Encounters

Planning activities for each class felt closely related to the gamemaster’s balancing act of creating encounters for their players. In D&D, each player controls a character with specific abilities set by their current level. As a character gains experience, they unlock more abilities as they reach the next level. The gamemaster has to make sure that at each level, the challenge of each encounter is commensurate with the players’ levels to keep them engaged.

For many weeks in the course, I highlighted a topic that would span two class periods that bookended the weekend. Before the first day, there would be a reading to introduce the topic, followed by a lecture at the beginning of the first day to expand on the topic (the background). Then, the students would work on an activity in class, most times in groups, that utilized the concepts presented in the introduction (an encounter). At the end of the activity, we would chat about the results and the related assignment that would be due the following week (rest and reflect). During that weekend, the students would have a short reading that was relevant to the topic and would complete their assignment (continued journey). On the second day for that topic, we would begin the class with a zero-stakes quiz that was based on the readings and mini lecture (another encounter). We then discussed the assignment submissions in a class critique, offering feedback and best practices in a safe setting (the aftermath). The last portion of the class would expand on the topic with one last activity on the topic (gain experience).

Being a Good Host

Just like sitting down for a game of D&D, when teaching your class, you are welcoming students into your space.  It’s not a space you own, but it is one in which you have control over the tone and the proceedings. As a good host, whether for a dinner party, a classroom activity, or a D&D adventure to clear out a cave of kobolds, you must be aware of how your guests are responding to the experience. In the case of D&D, that means being aware of how each player is interacting and contributing to the story you are building together. From the classroom perspective you should be similarly mindful of student engagement and progress. You can achieve this not only with summative assessments (the results from quizzes, assignments, etc.) but also formative assessments (ungraded quizzes, surveys, etc.). For example, a mid-semester survey can help inform you of what the students are enjoying about the class, what could make it better, and any issues with the content that they are having trouble with.

Side Quests

The concept of a Side Quest in gaming refers to an optional task to achieve a supplemental benefit for your character. I used this concept to offer extra-credit assignments that would allow the students to gain bonus points towards assignments, participation, or the final project. The Side Quests provided the opportunity for the students to reengage with the content, give them more data visualization practice, or reflect deeper on topics. The following are examples of a few of my favorite Side Quest assignments:

  • “Find the Gestalt!”: Students find a data visualization and describe what gestalt technics were used and where. This provided more practice identifying technics in the wild.
  • “You be the Instructor!”: Students develop up to five challenging quiz questions from the course content that had accurate answers. This allowed them to think deeper about a topic.
  • “Journal of the Journey!”: Students submit pages from their class notes/sketchbook. This incentivized them to record tidbits from class that they found interesting, which gave me feedback on the parts of the course that resonated with the students.

Final Thoughts

D&D helped me to pull from years of experience as a gamemaster. In the end, as long as you are thoughtfully guiding your participants/students/adventurists to new heights through balanced challenges, they will all surely level up to be ready for their next adventure.

Reid Sczerba, Digital Solutions Designer
Center for Teaching Excellence and Innovation

Image Source: Reid Sczerba, Pixabay

This blog post was adapted from the full article, “Lessons from a Gamemaster,” which is part of our printed Innovative Instructor series.

Lunch and Learn: Generative AI – Teaching Uses, Learning Curves, and Classroom Guidelines

Posted on by
Reply

On Tuesday, October 3rd, the Center for Teaching Excellence and Innovation (CTEI) hosted its first Lunch and Learn of the academic year, a panel discussion titled, “Generative AI: Teaching Uses, Learning Curves, and Classroom Guidelines.” The three panelists included Jun Fang, Assistant Director of the Instructional Design and Technology Team in the Carey Business School, Carly Schnitzler, KSAS instructor in the University Writing Program, and Sean Tackett, Associate Professor in the School of Medicine.  The discussion was moderated by Caroline Egan, project manager in the CTEI. Mike Reese, director of the CTEI, also helped to facilitate the event. 

The panelists began by introducing themselves and then describing their experiences with generative AI. Jun Fang loves new technology and has been experimenting with AI since its inception. He noticed the faculty that he works with generally fall into two categories when it comes to using AI: some are quite concerned about students using it to cheat and are not ready to use it, while others see a great deal of potential and are very excited to use it in the classroom.  In speaking with colleagues from across the institution, Fang quickly realized these are common sentiments expressed by faculty in all JHU divisions. This motivated him to lead an effort to create a set of AI guidelines specifically geared toward faculty. The document contains a number of strategies for using AI including: designing engaging course activities, providing feedback for students on their assignments, and redesigning course assessments. The section on redesigning course assessments uses two approaches: the “avoidance approach,” which involves deliberately designing assessments without AI, and the “activation approach,” which intentionally integrates AI tools into the curriculum. The document includes specific examples of many of the strategies mentioned as well as links to widely used generative AI tools. 

Fang described a recent scenario in which a faculty member was concerned that students were using ChatGPT to generate answers to online discussion board questions.  To mitigate this situation, Fang suggested the faculty member revise the questions so that they were tied to a specific reading or perhaps to a topic generated in one of his online synchronous class sessions.  Another suggestion was to have students submit two answers for each question – one original answer and one generated by ChatGPT – and then have the students compare the two answers.  The faculty member was not comfortable with either of these suggestions and ended up making the discussion more of a synchronous activity, rather than asynchronous.  Fang acknowledged that everyone has a different comfort level with using AI and that one approach is not necessarily better than another.     

Carly Schnitzler currently teaches two introductory writing courses to undergraduates and is very open to using generative AI in her classroom.  At the start of the semester, she asked students to fill out an intake survey which included questions about previous writing experiences and any technologies used, including generative AI. She found that students were reluctant to admit that they had used these technologies, such as ChatGPT, for anything other than ‘novelty’ purposes because they associated these tools with cheating. After seeing the results of the survey, Schnitzler thought it would be beneficial for students to explore the potential use of generative AI in class. She asked students to do an assignment where they had to create standards of conduct in a first year writing class, which included discussing their expectations of the course, the instructor, their peers, and how AI would fit in among these expectations. The class came up with three standards: 

  1. AI tools should support (and not distract from) the goals of the class, such as critical thinking, analytical skills, developing a personal voice, etc.  
  2. AI tools can be used for certain parts of the writing process, such as brainstorming, revising, or editing, but students must disclose that AI tools were used. 
  3. If there appears to be an over-use or over-reliance on AI tools, a discussion will take place to address the situation rather than disciplinary action. (Schnitzler wants students to feel safe exploring the tools without fear of repercussion.) 

This assignment comes from an open collection of cross-disciplinary assignments that use text generation technologies, mostly in a writing context. TextGenEd: Teaching with Text Generation Technologies, co-edited by Schnitzler, consists of freely accessible assignments submitted by scholars from across the nation. Assignments are divided into categories, such as AI literacy, rhetorical engagements, professional writing, creative explorations, and ethical considerations. Most are designed so that the technologies used are explored by students and instructors together, requiring very little ‘expert’ technological skills.  Schnitzler noted that there is a call for new submissions twice each year and encouraged instructors to consider submitting their own assignments that use text generation AI.

Sean Tackett was initially fearful of ChatGPT when it was released last year. Reading article after article stating how generative AI was going to “take over” pushed him to learn as much as he could about this new technology. He began experimenting with it and initially did not find it easy to use or even necessarily useful in his work with medical school faculty. However, he and some colleagues recognized potential in these tools and ended up applying for and receiving a JHU DELTA grant to find ways they could apply generative AI to faculty development in the medical school. Tackett described how they are experimenting with generative AI in a curriculum development course that he teaches to the med school faculty. For example, one of the tasks is for faculty to learn to write learning objectives, so they’ve been developing prompts that can be used to specifically critique learning objectives. Another example is developing prompts to critique writing. Most of Tackett’s students are medical professionals who do not have a lot of time to learn new technologies, so his team is continually trying to refine prompts in these systems to make them as useful and efficient as possible. Despite being so busy, Tackett noted the faculty are generally enthusiastic about having the opportunity to use these tools.     

The discussion continued with a question and answer session with audience members: 

Q: How do we transfer and integrate this knowledge with teaching assistants who help manage the larger sized classes? What about grading?
ST: I would advocate for the potential of AI to replace a TA in terms of grading, but not in terms of a TA having a meaningful dialogue with a student. 
JF: Generative AI tools can be used to provide valuable feedback on assessments. There are a lot of tools out there to help make grading easier for your TAs, but AI can be used for the feedback piece. 

Q: How might professors provide guidelines to students to use generative AI to help them study better for difficult and complex topics?
MR: One possibility is to generate quiz questions – and then have students follow up by checking the work of these quizzes that have been generated.
CS: Using a ChatGPT or other text generation tool as a reading comprehension aid is something that has been useful for non-native English speakers. For example, adding a paragraph from an academic article into ChatGPT and asking what this means in plain language can be helpful.

CE: This gets to what I call ‘prompt literacy,’ which is designing better prompts to give you better answers. There is a very good series about this on Youtube from the University of Pennsylvania.
Sean, what have you experienced with prompting right now, in terms of challenges and opportunities?
ST: We’re trying to put together advice on how to better prompt the system to get more refined and accurate answers. After a few iterations of prompting the system, we refine the prompt and put it into a template for our faculty, leaving a few ‘blanks’ for them to fill in with their specific variables. The faculty are experts in their subject areas, so they can tell if the output is accurate or not. We’re in the process of collecting their output, to put together best practices about what works, what does not work.  

CE: What would you all like to see in terms of guidelines and best practices for AI on a web page geared towards using AI in the classroom?
Guest: And along those lines, how to we move forward with assigning research projects, knowing that these tools are available for students?
ST: I think it could be useful for students to learn research skills. They could use the tools to research something, then critique the results and explain how they verified those results. It can also be useful for generating ideas and brainstorming. Another thought is that there are a number of domain specific generative AI databases, such as Open Evidence which is useful in the medical field.  
CS: To Sean’s point, I think a comparative approach is useful with these tools. The tools are very good at pattern matching genre conventions, so doing comparative work within a genre could be useful.
JF: I think ChatGPT and other generative AI tools can be useful for different parts of the research process, such as brainstorming, structure, and editing. But not for something like providing or validating evidence.  

Q: As a grad student, I’m wondering how the presence of AI might force us to refine the types of questions and evaluations that we give our students. Are there ways to engineer our own questions so that the shift of the question is changed to avoid the problem [of having to refine and update the question] in the first place?
CS: There is an assignment in our collection that talks about bringing an assignment from past to present. Again, thinking in terms of a comparative approach, ask ChatGPT the question, and then ask your students the same question and see how they compare, if there are any patterns.  I think it can be helpful to think of ChatGPT as adding another voice to the room.
JF: We have a section in the guidelines on how to redesign assessment to cope with generative AI related issues. We suggest two approaches: the avoidance approach and the activation approach. The avoidance approach is for faculty who are not yet comfortable using this technology and want to avoid having students use it.  One example of this approach is for faculty to rework their assignments to focus on a higher level of learning, such as creativity or analysis, which will hopefully reduce or eliminate the opportunity for students to use AI tools. The activation approach encourages faculty to proactively integrate AI tools into the assessment process. One example of this approach I mentioned earlier is when I suggested to a faculty member to rework their discussion board questions to allow students to submit two versions of the answers, one created by them and the other by ChatGPT, and then analyze the results. 

Q: What is the ultimate goal of education? We may have different goals for different schools. Also, AI may bridge people from different social backgrounds. In China, where I grew up, the ability to read or write strongly depends on the social status of the family you come from. So there is some discomfort using it in the classroom.
CS: I feel some discomfort also, and that’s what led to the development of the guidelines in my classroom. I posed a similar question to my students: if we have these tools that can allegedly write for us, what is the point of taking a writing class?  They responded by saying things like, “writing helps to develop critical thinking and analytical skills,” to which I added, “being here is an investment in yourself as a student, a scholar, and a thinker.” I think asking students to articulate the value of the education that they want to get is really helpful in determining guidelines for AI.
ST: Going to school and getting an education is an investment of your time. You pay now so you can be paid later. But it’s not as transactional as that. AI is already in the work environment and will become more prevalent. If we’re not preparing students to succeed in the work environment, we are doing them a disservice. We teach students to apply generative AI in their classes so they are prepared to use it in the workforce.
JF: In the business school, everything is market driven. I think education can fit into that framework as well. We’re trying to provide graduates with the confidence they need to finish the work and meet the market’s need. We know that generative AI tools have really changed the world and they’re starting to emerge in every part of our life. We need to train students to realize that ChatGPT might be part of their education, part of life in the future, and part of the work in the future as well. There are things AI can help us do, but there are still fundamentals that students need to learn. One example is calculators: we still need to learn from the beginning that 1 + 1 = 2. 
CE: This question also reminded me of asking your students, what is the ultimate purpose of a research paper? Where do they think ChatGPT should fit into the research process?  

Q: I work at the library and we’re getting lots of questions about how to detect if students are using AI. And also, how do you determine if students are relying too heavily on AI?
JF: We also get this question from our faculty. The most used detection tool right now is Turnitin, which is embedded in Canvas. But the level of accuracy is not reliable. We encourage faculty to always validate before accepting the results.  For faculty who are actively using AI in the classroom, we also encourage them to provide clear guidance and expectations to students on how they are allowed to use it.  This may make it a little easier to determine if they are using it correctly or not.
MR: There are some other tools out there, such a GPTZero, ZeroGPT, but to Jun’s point, the difficult thing is that it’s different than plagiarism detection which says this is copied, and here’s the source. These tools say there’s a probability that part of this was taken, but you can’t point to a direct source. It’s up to instructors whether or not to use these tools, but consider using them to facilitate a conversation with students. In my own classes if I suspect academic misconduct, I usually start by asking them to explain, talk to me about what is happening before I make accusations. With these tools, there tends to be no hard evidence, just probabilities that something may have happened.  This is definitely an area we’re all still learning about.
Guest: I was just thinking that having a conversation with students about why they are turning to the tool in the first place might prevent misconduct.  Instead of sending them to an academic misconduct committee, we could have these conversations, like Carly mentioned. Making students aware of the limitations of the tool could also be helpful.
CS: Yes, I say that in our guidelines that I’m prioritizing conferences with students over immediate disciplinary action. I try to pre-empt anxiety students might feel around using these tools. Designing your assignments in a way that reduces anxiety is also helpful. For example, I tend to design assignments that build on one another throughout the semester in smaller bits, rather than one giant chunk all at once.  

Q: Is there any discussion around combining AI with teaching, such as generating personalized explanations of a topic? Students will have different levels of expertise and comfort with different topics.
ST: We’re trying to do this, to create a teaching aid for the future. We’re planning to use it to create assessment items.  

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation 

Image Source: Pixabay, Unsplash

 

Adapting to AI in the Classroom for Time-Strapped Instructors

Posted on by
Reply

In the past few months, we have spoken to many instructors – faculty, graduate students, even undergraduate teaching assistants –  who are doing very interesting things with artificial intelligence tools in their classes this coming fall. Some are writing grants to support research into classroom uses of AI, some are designing interactive online modules to help teach about the ethics of AI, and some are integrating AI tools into their instructional activities.

This blog post is for another instructor population: those that have not had the time or capacity to redevelop their courses, their assessments, or their activities to accommodate an AI world. “Redesigning assessments with AI in mind” might be the 20th item on a long list of to-dos for the coming semester. Adapting to new technologies that could change the classroom experience – and AI is certainly one of them – seems like an overwhelming task. Classes start in one week, and wrestling with the teaching and learning opportunities and challenges of artificial intelligence may not be an achievable goal.

However, there are some concrete steps and curated resources to take into account in terms of AI when planning and teaching your courses.

Recommendations for Starting with AI

Here are six recommendations (and one extra credit assignment). Following all of these suggestions will put you on good footing with the learning curve associated with AI in the classroom, but even doing one or two is a good way to start.

  1. Experiment with ChatGPT and other AI tools. Just get in there and start using them and see what they produce. In an article for the Chronicle of Higher Education, one writer said, “I started by reminding myself, anytime I was about to Google something, to ask ChatGPT.”[1] ChatGPT-ing (or using Google Bard) instead of Google-ing is a good on-ramp to AI usage. You may even find them useful to you as an instructor. Here are four basic generative AI models to start with along with prompt suggestions:
    1. ChatGPT – The first (and by some reports, still the most accurate) text-based generative AI. Prompt suggestion: Ask a basic question about teaching, e.g., “How can I grade exams more efficiently?” or “How can I provide written feedback more efficiently?”
    2. Google Bard – Less text-heavy than ChatGPT; potentially geared towards more logic-based questions, e.g., “How do I create a website in WordPress?”
    3. Microsoft Bing – Able to generate images as well as text and simultaneously harness the power of a search engine. Potential question: “Name the characteristics of neo-classical architecture and provide an example.”
    4. Fotor.com – Image-generator AI. Potential question: “Provide an illustration for my chemistry class syllabus.”
  2. Run your assignments through an AI tool. This will help benchmark possible AI-generated responses to your assignments. More sophisticated AI users will engage in prompt engineering that could make uncited or incorrect usage of AI harder to detect, but getting at least one example of an AI response is helpful. It will not only provide a sightline into possible academic integrity issues but also point to whether your assignment may need to be revised or redeveloped, which could include integrating AI itself. Derek Bruff, a writer and higher education consultant, provides good guidance on assessment design in light of AI:
    1. Why does this assignment make sense for this course?
    2. What are specific learning objectives for this assignment?
    3. How might students use AI tools while working on this assignment?
    4. How might AI undercut the goals of this assignment? How could you mitigate this?
    5. How might AI enhance the assignment? Where would students need help figuring that out?
    6. Focus on the process. How could you make the assignment more meaningful for students or support them more in the work? [2]
  3. Add an AI policy to your syllabus. This may require doing some or all of the recommendations above, but even if you do not have the capacity to take a deep dive into AI tools before courses start, it is a good idea to take a stab at a policy, even if it is brief. As mentioned above, you will be adapting this policy fairly quickly. The sooner you develop a benchmark policy and determine what works and what does not, the better. Lance Eaton, a doctoral student in higher education at the University of Massachusetts at Boston, has crowdsourced a Google Document with many helpful examples of AI policies for syllabi. This is an excellent place to start.
  4. Determine your academic integrity policy for AI. This may be part of your general AI policy or it could be separate. Regardless, this will probably be V.1 of your academic integrity policy, but again, starting now will put you in a good position to iterate as needed. To start, review Academic Integrity Policies for Johns Hopkins Schools. Lance Eaton’s Google Document (above) has many examples of AI policies that include academic integrity statements.
  5. Teach your students how to cite AI tools. This information could be incorporated into a syllabus policy and/or academic integrity policy, but correct citation – at least according to August 2023 recommendations of these style guides – is step number one. Making your students aware that they need to cite uses of AI tools and giving them the tools for doing that will (hopefully) incentivize compliance with your academic integrity policies.
    1. APA Citation Guidance – ChatGPT
    2. MLA Citation Guidance – Generative AI
    3. Chicago Style Citation Guidance – ChatGPT
    4. Johns Hopkins Library Guide on Citation
  6. Talk to your local center for teaching and learning. All Hopkins Schools have teaching and learning centers, some have been publishing guidance on how to teach and learn with artificial intelligence tools, and many have been considering the possible consequences of AI in the classroom. Here’s a list of teaching and learning centers at Hopkins, and here are two rich resources developed by two CTLs at Hopkins:
    1. Teaching & Learning in the ChatGPT Era. This website was created by the Center for Learning Design & Technology at the Whiting School of Engineering. It provides a great overview on generative AI as well as providing guidance on academic integrity questions, student use of AI, and assessment design with AI. Kelly Orr, Nathan Graham, Olysha Magruder, Mel Rizzuto, and Edward Queen of the CLDT all contributed to the website as did adjunct faculty David Porter.
    2. Johns Hopkins University Generative AI Tool Implementation Guidance and Best Practices. Jun Fang, Assistant Director in Teaching & Learning@Carey in the Carey School of Business led the development of this resource with contributions from representatives at other schools and teaching and learning centers at Hopkins. This guide provides substantial guidance on using generative AI to design engaging course activities, provide assignment feedback, and gives a list of AI tools for higher education.

Extra credit assignment for those with a little more capacity:

  1. Learn a little about prompt engineering. Prompt engineering is developing and refining questions and statements for AI models such that they generate results with the desired specificity, tone, length, citations, etc. This will give you a sightline into AI capacities beyond a simple one-time command (e.g., “Compare and contrast models of femininity in Shakespeare’s Much Ado About Nothing and Taming of the Shrew”) which may yield an overly broad answer that lacks specificity and nuance. Prompt engineering will also help you learn to direct and guide AI models and not just react to them. For a useful beginner’s guide to prompt engineering, check out the brief video on prompting AI from Wharton School instructors.

Why You Should Do This

Here is why you should take the (small) leap: Artificial intelligence will change the way we teach and learn. The internet did this, email did this, and so will AI. Taking small steps to acculturate to this new reality is the best way to build the flexibility needed to successfully teach and learn with AI – and, very importantly, teach your students how to teach and learn with AI. Here are more reasons to begin to shift your behavior:

  • You can start small. Take this semester as an opportunity to begin to build your AI teaching and learning skills. You do not have to overhaul your syllabi or classroom activities to accommodate AI; you just have to begin to think through the implications of teaching in a world where AI tools are easily available and could pass your homework assignments. Ask yourself how you would coach students encountering your subject matter for the first time, and then apply those principles to your own learning about AI.
  • You will have to learn to adapt quickly. Artificial intelligence tools are evolving rapidly; your course design and instructional approach will do so, too. Each semester will require additional revisions to your syllabi to accommodate our increasing use of AI tools and AI’s increasing capacities. Starting to build those muscles now with lower-effort activities will pay off in the long run.
  • You actually know how to do this. Researching? Developing hypotheses? Evaluating resources? Check, check, and check. Iterating, revising, and adapting as you go along? Teaching students how to evaluate resources? Guiding students to think about the definitions of “artificial,” “intelligence,” and “human”? Check all that, too. The skills required to become AI-literate from a teaching and learning perspective are skills you already have. It is just a matter of applying them to this particular challenge/opportunity/problem (however you frame it).

Finally, give yourself and your students some grace. This is a huge part of beginning to learn how to teach and learn in an AI world; most likely, neither you nor your students will be proficient AI practitioners this semester. You may miss an academic integrity issue or overlook good opportunities to use AI in a classroom activity. Your students may not cite AI correctly or may not cite it at all. They may be far more fluent with AI than you are, or they may be too trusting of AI. Whatever happens, try to remember that you all are new at this and, as new learners, you all may take missteps and make mistakes with the technology.

Caroline Egan
Caroline Egan is a Project Manager in the Center for Teaching Excellence and Innovation, supporting instructional training and development for Hopkins faculty, graduate students, post-doctoral fellows, and staff.

[1] Darby, Flower. (27 June 2023). 4 steps to help you plan for ChatGPT in your classroom. The Chronicle of Higher Education. https://www-chronicle-com.proxy1.library.jhu.edu/article/4-steps-to-help-you-plan-for-chatgpt-in-your-classroom

[2] Bruff, D. (19 July 2023). Assignment makeovers in the AI age: Essay edition. Agile learning: Derek Bruff’s blog on teaching and learning. https://derekbruff.org/?p=4105

Selected Resources

From Hopkins:

Additional resources:

Image Source: Unsplash

Lunch and Learn: Community-Based Learning

Posted on by
1

On Wednesday, April 19th, the Center for Teaching Excellence and Innovation (CTEI) hosted a Lunch and Learn on Community-Based Learning. Luisa De Guzman, Assistant Director of the Center for Social Concern, moderated a panel of faculty from the Engaged Scholar Faculty and Community Partner Fellows Program. Sponsored by the Center for Social Concern, this program supports partnerships between JHU faculty and leaders from Baltimore City non-profits in co-teaching Community-Based Learning courses. The panel included: Anne-Elizabeth Brodsky, Associate Teaching Professor in the University Writing Program, Alissa Burkholder Murphy, Senior Lecturer in Mechanical Engineering, Jasmine Blanks Jones, Executive Director of the Center for Social Concern, Matthew Pavesich, Teaching Professor and Director of the University Writing Program, and Victoria Harms, Visiting Assistant Professor in History.

De Guzman opened the presentation by describing community-based learning (CBL) and the opportunities available at the Center for Social Concern. CBL is a pedagogical model that integrates student learning with community engagement. It provides students the opportunity to apply what they are learning in real-world settings and reflect on their service experiences within a classroom setting. By partnering with community organizations, students, faculty, and community stakeholders benefit from the collaborative experience of pursuing mutual goals (Kuh, 2008).

The Engaged Scholarship program at the Center for Social Concern offers various ways to encourage faculty to integrate CBL into their teaching; opportunities range from mini grants of $500 to support CBL activities to an award of up to $5000 with the Engaged Scholar Faculty Fellows program to develop CBL courses with partners in the community. The Spring 2023 Engaged Scholar Faculty Fellows on the panel taught the following courses:

  • Anne Elizabeth Brodsky: Reintroduction to Writing: Music, Young People, and Democracy
  • Alissa Burkholder Murphy: Social Impact Design
  • Jasmine Blanks Jones: Black Storytelling: Public Health Education in the Black World
  • Matthew Pavesich: Reintroduction to Writing: The City that Writes
  • Victoria Harms: Rebels, Revolutions, and the Right-Wing Backlash

De Guzman continued with a question-answer session with panelists, including questions and discussion with audience members.

Q: Describe integrating CBL into your course, and what motivated you?

VH: I heard a talk by Dr. Shawntay Stocks on CBL in 2018. I was relatively new and did not feel very comfortable on the Homewood campus at that time. But my students began asking me more and more questions about Baltimore. CBL offered an opportunity to bring Baltimore into my course from different viewpoints.
MP: I started thinking about how to connect goals in our classroom with the community. Grade school kids, including high schoolers, take courses in storytelling. The partners for us have been students in their late teens and early twenties from all across Baltimore City.  CBL allows me to bring peers to my students from the community.
JBJ: Prior to my current position, I ran a nonprofit in West Africa for twelve years and recognize that the stories, knowledge, and ancestral wisdom of people of color across the globe is intentionally left out of Western academic practices. If we’re going to really think about the cultivation of knowledge, we have to engage with our communities, with people who are doing the work, who are finding solutions. That is my commitment. This is where it starts if we’re going to be better humans, researchers, and scholars.
AEB: I really like the way CBL expands students’ sense of what an education is and also what is considered expertise. Educators are not just those with a particular degree, but include others who are outside of the classroom: administrators, performers, musicians, etc. CBL also helps students expand their sense of what it means to be in college and not be defined by their major or a particular class. It helps them understand what they could learn in the moment, instead of five years from now. It also gives students an interdisciplinary experience and encourages them to question the idea of disciplinary boundaries.
ABM: I teach a year-long multidisciplinary design course where students work with an external project partner for two semesters.  Students like working on social impact projects, being part of something bigger than themselves. I was hesitant at first to bring these types of projects to students without the proper resources; I had some experience working overseas and recognized the challenges of projects like these. The Faculty Fellows program has great structure. It takes massive amounts of time, almost like having a part-time job, but it’s been a great platform to work with Baltimore City Rec and Parks.

Q: How did you manage the logistical side of starting up the partnerships and managing the relationships with the organization you worked with?

MP: It was a rough introduction with Wide Angle Youth Media at first. I came in with a pedagogical model that I had used previously, where students produce work for the organization. The organization’s response was slightly cold – they weren’t sure about our involvement. I stepped back and adjusted assignments and reconfigured the syllabus. We kept communicating which built up trust and things gradually improved. This is all part of the inherent messiness and flexibility that we as teachers have to be ready for.
AEB: I was brand new to OrchKids. My kids play music, so I was familiar with the program, but I was new to them. Once they (OrchKids) got the ‘okay’ to go through with it, we set up weekly Zoom meetings. The logistics were taken care of by Luisa De Guzman.
VH: Finding partners is a challenge and may be a deterrent. You have to acknowledge the legitimate reservations that people have about working with Hopkins. Positionality and cultural humility are lessons that I took away for myself. As a white woman from Hopkins I would show up in certain spaces in Baltimore and not always be welcome. After months of going to events and talking to people, I was able to make a connection at the Reginald F. Lewis Museum. Like Matt said, you keep building on the relationships.
Q: Do these organizations approach the Center for Social Concern (CSC)? Or is it an organic process?

JBJ: It’s generally an organic process. Luisa is very diligent about not matching people with organizations, or vice versa, but with establishing connections and helping people find their way together. We have a lot of community partners that span our different programs. And we’re looking at ways to continue to encourage more. We’re doing this through community happy hours with our partners and bringing people together just to get to know each other, to see what sparks and what ideas can come into fruition.
ABM: I had a booklet of past projects that I looked through and sought out partners that might have something to do with engineering. I reached out and asked if anyone had contacts, made a few calls, and figured out a project from there.
MP: One thing I found a little surprising – my students got a sense of higher stakes in the class. With the addition of the community partners, it’s like the tent got bigger. The stakes got a little higher, while still being relatively safe enough for novice writers. They realized, “We’re doing something cool. It matters to people more than just us.”

Q: How do you assess student learning in the CBL course?

AEB: The work that was going to get evaluated was the work of writing. I asked the folks at OrchKids if there was something our students could do for them in terms of writing or researching, but there was not.
MP: The answer to the question, which is a great question, depends on the pedagogical context of the content. CBL is essentially introducing students to a context for writing and a community for doing that.
VH: In my class, an upper-level writing intensive History class, there are reading assignments about Baltimore’s history in the 1960s. There are also two research papers, one of which is on Baltimore.  At the end of the semester, I asked students, “What do we do about the participation grade?”  I asked them to decide how they wanted to be assessed on participation and I walked out of the room. When I walked back in, they had a whole argument laid out about why they each deserved 100%. But it was a meaningful argument, so I was fine with it.
JBJ: It’s a real struggle in my course because I have students from many disciplines (public health, anthropology, theatre, etc.). There are public health outcomes that are central points to the course, but also historical content they are exposed to during the engagement with the community. It becomes an evaluation of the discussions that take place in the community, about the readings, and reflecting with each other.

Q: Is anyone documenting this pedagogy?

MP: UWP is constructing a digital resource for teaching and writing: “The Teaching and Writing Toolkit.”  It will contain some subsections about CBL, including community engaged syllabi, writing assignments, and rubrics that folks would need to evaluate this work.
JBJ: We’d like to move towards doing research about our practice and write about it. That’s a direction that we are excitedly heading in.
VH: We are a data-driven institution. I added extra questions on the course evaluations and published an article. You do it through publications.

Q:  One of the challenges of incorporating CBL is the budget and how it goes into the community. And what happens once the funding ends?

JBJ: As a Faculty Fellow you receive $5000 to work with – this can cover a range of things like materials to student transportation. In my case, the money went to transporting my students and the rest of the balance went to my community partner, the Blacks in Wax Museum. In terms of what happens after we’re done, Anand Pandian in Anthropology found a way for his community co-instructor to become a lecturer at Hopkins. It’s on us as faculty to really advocate for these opportunities. We also need to have more ways to build in how we apply for [CBL] grants together. I am hopeful there will be more happening in the way of tenure and promotion that allows faculty to count engaged scholarship and public facing scholarship.
Q: If students are already involved with an organization, is there a way for them to be recognized (with credit or other) for their efforts so that it also becomes a student-driven initiative?

JBJ: I’ve had students do independent studies with me for credit. These students often remain engaged in the work beyond the initial encounter and sometimes end up working as interns at the CSC.
MP: One of the recommendations from CUE2 is about bringing students’ curriculum, co-curricular, and extra-curricular experiences closer together. We need to stand up credit bearing experiences for students that are not just issued from academic offices, but from experiential learning experiences. This is happening across the country. We could position ourselves as leaders in this area.

Q: I feel like the K-12 environment has been doing this work for a long time. How much do you feel like you’re learning from the K-12 space?

MP: It might be telling about the insularity of Higher Ed that I’m thinking to myself, I’m not really familiar with the conversations happening in Primary and Secondary Ed around those ways.
JBJ: The School of Education is taking innovative steps with how they assess their grad students. They are accepting portfolios rather than just a straightforward dissertation. I think there’s movement there, more so with the profession than with the disciplines, which isn’t surprising. In the professions, in nursing and medicine, narrative medicine has been a thing for a very long time. Now there are reports from national academies about how we use a variety of forms of knowledge creation beyond solely the written text. It comes down to how you evaluate it, not just the long-written paper.

Q: Please tell us a word that summarizes your community-based learning experiences thus far.

VH: Cultural humility.
MP: Potential. We got started, something happened. But the future version of it is the most exciting version, I think.
JBJ: Reparative, and beyond just the relational physical repair.
AEB: Plaid. Some of it was a mess, some of it was personal, and it was all very political. So when you put that together, you get “plaid.”
ABH: Hopeful. There are positive responses from the students, and I think that good things are going to come from what they’re producing.


References:
Kuh, George D. (2008). “High-impact educational practices: What they are, who has access to them, and why they matter.” AAC&U, Washington, D.C. 34 pp.

 

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation

Image Sources: Lunch and Learn Logo, Pixabay

Lunch and Learn: First-Year Seminars

Posted on by
Reply

On February 15, 2023, the Center for Teaching Excellence and Innovation (CTEI) and the First-Year Seminar program hosted a Lunch and Learn with a panel of faculty members to share their experiences teaching First-Year Seminars (FYS) in the Fall of 2022 as well discuss emerging best practices. The panel included Christopher Celenza, Dean of the Krieger School of Arts and Sciences, and Professor of History and Classics; Marisa O’Connor, Associate Teaching Professor, University Writing Program; Lilliana Mason, SNF Agora Institute, Associate Professor of Political Science; and Karen ní Mheallaigh, Professor of Humanities, Classics Chair. Aliza Watters, Assistant Dean for the Undergraduate Curriculum and Director of First-Year Seminars, moderated the discussion.

Dr. Watters began with a short introduction to the FYS program, as well as some high-level reflections on lessons learned from Fall 2022. Part of a series of curricular recommendations from the Second Commission on Undergraduate Education (CUE2), FYS welcomes students to the university in a small cohort experience (12 students per seminar), each one unique, but with shared goals focused on intellectual rigor and curiosity, peer community, and faculty-student interaction and mentorship. FYS were first piloted two years ago in the Fall of 2020; since then there have been over sixty FYS piloted. The Fall 2022 semester was the first semester where FYS were required for all incoming students in the Krieger School of Arts and Sciences. Seminars are three credits, students are graded Satisfactory/Unsatisfactory (S/U), and faculty form communities of practice each fall to discuss and learn from experiences across the approximately 75 courses. Watters shared student survey results from Fall 2022 which averaged or exceeded 90% for intellectual experience, connection with faculty, and overall enjoyment.

The presentation continued with each faculty panelist briefly describing their seminar, including approach, highlights, and something learned along the way.

Dean Celenza began with his course, Books, Authenticity, and Truth, which examines the search for truth among selected texts from Roman antiquity through the mid-17th century. Unique to the seminar and most memorable for students were the weekly hands-on encounters they had with texts in the library’s rare books collection, an experiential learning component that complemented the analytical discussions. Early in the semester, Dean Celenza reckoned with the difficulty of some of the sources he was assigning. Rather than a formal introduction to his field, with a focus on developing discipline-specific, complex knowledge, he considered the ethic of the group’s learning in the moment – and the personal and communal stakes of that learning. For him, it was more important to meet students “where they are” in terms of background knowledge rather than try and cover every detail. He also commented that he so enjoyed getting to know his students more personally in the context of FYS, that the S/U grading scheme is essential to this, and how, institutionally, FYS enables faculty to have a far richer understanding of the overall landscape experienced by our first-year students.

Professor Mason continued with her seminar, The Psychology of Mass Politics in the United States. Her course focused on the various misperceptions we have about how people make decisions based on politics, how our thoughts can be influenced and biased through deliberate misinformation, and in getting students to note these practices in the real world. Mason purposely varied the way she presented material to students, regularly using film, video, and podcasts in addition to journal articles, and alternating weeks of heavier and lighter reading. One particularly enjoyable assignment for students was to design and develop a false story about Johns Hopkins University as a way of self-consciously inoculating them against misinformation. Surprised at the divergent levels of basic political knowledge students had coming into her class, including the different branches of government, Professor Mason plans to include more introductory material going forward and even more attention to annotated reading practices. Like Dean Celenza, Mason enjoyed getting to know her students and began all her classes with a more personal check-in before turning to the week’s material.

Dr. O’Connor continued with her course, Is a Corporation a Person?, which presents students with a legal framework for examining personhood and its related rights to free speech in the U.S. The seminar asks students to examine this concept from various viewpoints, including other cultures, political movements, and literature. Dr. O’Connor draws on a great diversity of sources for her students to analyze: film, photographs, political cartoons, websites, and scholarly articles, among others. At one point during the course, O’Connor asked students to read articles by two scholars who had vastly different opinions about a particular subject; students were incredulous that these “experts in the field” were disagreeing with each other so starkly. Dr. O’Connor noted how transformative this experience can be for students: to see intellectual disagreement so explicitly rendered and to be invited, themselves, into the scholarly conversation. And that is how Dr. O’Connor’s course culminates: with each student proposing a research question and project that engages debates of personhood.

Professor ní Mheallaigh described her course, Lunar Histories, as imagining the moon as a magic door or portal for students: how it was perceived by ancient people, how it factored into religious practices, and how it eventually emerged into scientific literature and later became a lodestar for truth in the modern world. Professor ní Mheallaigh found that students enjoyed the interactive parts of the seminar best. To help them process ancient material that could be dense, or overly-technical, she regularly asked students to draw or otherwise visualize what they thought the author was trying to convey in early texts. Another activity that was especially memorable for students was going to the JHU Archeological Museum to examine various ancient artifacts, including a wand used to cast spells. These active learning practice helped take the pressure off of having to comprehend every historical detail while engaging students in the abiding imaginative components of lunar histories. Professor ní Mheallaigh also maintained that they helped engage the students emotionally as well as intellectually.

Lunch and learn panelists speaking.Dr. Watters summarized some of the emerging themes in the presentations and for FYS more broadly, including the need for source diversity and dynamism, modulating overly technical or discipline-specific content, incorporating experiential learning, and creating the space for more personal, low-key interactions between and among students and faculty. She then began the question-and-answer portion of the workshop which yielded active discussion with audience members. Here are some of the queries the panelists addressed:

Q: What is one concrete thing you did that worked really well?

CC: I asked students how they were doing and what was going on at the beginning of each class; it was a good way to “take the temperature” of the students and the room overall.
MO: I had students look at all sources we used in class, build a case, and present results. Finding evidence in the moment and figuring out how to talk about it worked well.
LM: Each week I had students do a written reflection asking what they learned, what questions they still have, etc.
KN: Examining ancient objects and exploring multimedia were very successful.

Q: I’ve heard from students that some FYSs are a lot of work. How did you all think about the work that you assigned to students?

KN: The feedback from my students was that the assigned work was actually light.
LM: I varied the workload each week. Sometimes there was a lot of reading, but then I lightened things up the next week with a podcast or some other activity. They seemed comfortable.
MO: I assigned different sources – documentaries, readings, etc. I tried to have them do something very short before class – fun and relatively easy – but enough that they were prepared to talk about something.
CC: I tried to keep assignments short. Short was key – I wanted to give all students a chance to participate.

Q: When you give writing assignments, do you comment on the writing? Are we trying to make these students better writers in FYS?

KN: Yes, I provided comments. I thought this was a core part of what we were doing and I wanted to help them.
CC: The fact that all students will take a writing-intensive course in the spring semester after their FYS (part of Krieger’s First Year Foundation of FYS plus First-Year Writing), takes the pressure off. I don’t think we need to spend too much time commenting on their writing.
LM: I graded all of my assignments complete/incomplete. I kept my comments at a higher level.
MO: I had the students focus on writing in smaller bits, which kept it doable for them, and therefore, not much commenting from me.

Another faculty member in the audience shared that when teaching his FYS, he included writing assignments where students had to write to different audiences, such as a letter to their parents or through the lens of an art critic. He said this kept them accountable to the sources, but that the versatility helped keep things “new and exciting” for students.

Q: Were students in your FYS from the same intended major or discipline, or were they varied in their academic interests?

A: All panelists said their students intended to major in different fields; the students seemed to realize FYS was their chance to try something different, outside of their intended major or its related requirements. Several students commented to their instructors that the FYS sparked a genuine interest in a new field of study for them.A group of faculty listening to Lunch and Learn panelists.

Q: Who can we contact if we have concerns about something going on with first-year students?

A: Dr. Watters responded that being receptive to student experiences in the context of FYS is crucially important and encouraged instructors to contact the students’ advisors if needed. She also noted the role FYS can play in understanding and responding to broader trends percolating among students.

Q, from another FYS faculty member: In one of my courses, I allow students to co-design the syllabus for the class. Although it can be scary, it also takes some of the pressure off of me, as the students tend to be more prepared for things. Did you design the whole course, or did you allow students to develop any of it?  

A: While none of the panelists allowed students direct involvement in developing their syllabi, some commented that they did give students varying degrees of freedom in their assignments (such as what sources to use), some authority over class discussions, and independence in final projects.

Q: What is something you hope your students got out of your class?

KN: I think the social dimension that is built into this environment is enormously beneficial. For example, I took my students to a local diner, Paper Moon on 29th Street. It was so simple, but I felt like I really got to know them.
CC: Students want to get to know their professors – they are looking for mentor relationships and FYS helps develop those.
MO: The S/U aspect and small size of the seminars supports the social aspect. Students felt comfortable talking to me about their first semester. I was a non-threatening person in their life, despite being one of their instructors. I really enjoyed getting to know them in this way.
LM: I agree, about getting to know the students. I’m already writing recommendation letters for some of them! My hope, though, is that they maintain a curiosity for and joy of learning.

Dr. Watters concluded the session by reading an anonymous quote from the FYS student survey:

My FYS was my favorite class. Most of my other classes were large lecture style classes with 200 people so engaging with 11 of my peers in a small seminar environment helped me build meaningful connections. The instructor was also fantastic and he really got to know me. This was not just a ‘fun’ class. It was a class that was instrumental to making my first semester enjoyable. I made at least 4 friends in my FYS. I went to Peabody and the Visionary Arts Museum with my FYS group and explored Baltimore. Equally as important, it challenged me a lot and I gained skills that are critical.

Aliza Watters
Assistant Dean for the Undergraduate Curriculum and Director of First-Year Seminars
Krieger School of Arts and Sciences

Amy Brusini, Senior Instructional Designer
Center for Teaching Excellence and Innovation

Image Sources: Lunch and Learn Logo, Beth Hals

A Faculty Follow-up Discussion: Re-engaging Students for the Fall Semester

Posted on by
Reply

On Tuesday, November 8th, the Center for Teaching Excellence and Innovation (CTEI) hosted a discussion on re-engaging students for the fall semester. At faculty request, this discussion was a continuation of one initially held in August, when participants explored the challenges they faced with the return to in-person teaching in Spring semester 2022. During that session, faculty offered potential ways to address disengagement in a student population who reported high levels of “stress, fatigue, and anxiety” in a post-pandemic world.male student staring at his computer This phenomenon has been noted in many media outlets, including The Chronicle of Higher Education, which recently hosted a webinar on addressing student disengagement and summarized it in a follow-up article. Mike Reese, Associate Dean and Director of the CTEI, moderated the conversation.  

The session kicked-off with instructors offering their general sense about how student engagement in their Fall courses compared to their Spring courses. The overall assessment was that problems remained, though there were some bright spots:  

  • One instructor noted that attendance in his course’s Friday session, led by teaching assistants, was down almost 50% in the recent week.  
  • Another noted that Fall was “a little bit” better than Spring, when she was still teaching online via Zoom, but she continued to observe a lot of “struggle” among her students, exacerbated by a lack of knowledge of how to address it.  
  • One participant, who regularly polled his students on their overall well-being on a scale from one to five with five being the highest score, said he was seeing a lot of ones and twos among his students. However, he started this practice during the pandemic so he didn’t have any pre-pandemic data to baseline the response.  
  • A fourth participant had observed that her students’ behavior was better, but they also had large gaps in their subject-matter knowledge due to the instructional disruptions incurred by the pandemic. 

Time management issues quickly became the dominant topic when one faculty member pointed out that this was a particular problem for his students. Other participants also offered examples of students struggling with time management; one faculty member said that she had received a lot of requests for extensions from students who admitted these were due to poor time management, and another said that she observed an all-senior class – usually a population with a good sense of time management –also contending with this issue.group of students socializing The reason for this, attendees speculated, may have to do with the full return to on-site courses and residential campus life. Students may be excited to dive back into campus life, trying to take advantage of opportunities, like lab-based research, not available during the pandemic, and becoming over-committed as a result. Another reason offered was that the time management skills needed to negotiate pandemic life and instruction needed to be re-adjusted for more typical university life.   

The post-pandemic gap in content-specific knowledge, particularly in the STEM disciplines, has prompted some academic programs to start looking at ways to make changes to their large introductory or gateway courses. One participant said her program was looking to make data-based adjustments informed by placement tests, in-person attendance at office hours, and data from Canvas classrooms and learning-support software, such as ALEKS. 

As a group, the participants generated several useful ideas to enhance engagement in both large lecture-style courses and smaller seminar courses:  

  • Increasing structure for small-group discussions in large classrooms: One instructor had added question prompts and a pre-identified spokesperson to her small-group break-out discussions to increase student focus, participation, and output during these sessions.  
  • Flipping one class meeting a week to start homework: Another instructor had flipped one class meeting a week to provide students with a pre-determined timeslot in which to start their homework each week and receive real-time instructional feedback. This helped students with time management and on-time completion of the homework.  
  • Requiring a one-to-one meeting outside class: An attendee required that seminar students meet with him one-on-one at least once outside of class, which helped build relationships and comfort with class participation.  
  • Requiring student socialization outside class: A participant volunteered onegroup of students smiling approach that she heard about via the Chronicle Webinar: to require that students meet and socialize outside of class twice a month to work on “conversation fundamentals” – how to have a balanced conversation, how to use open-ended questions – to build “social sophistication and stamina” in in-person environments post-pandemic. 
  • Mid-semester surveys: Two instructors distributed mid-semester surveys to students that specifically targeted issues of classroom engagement, and one queried participants about their time-on-task for assignments and activities. Though survey participation was low in one course, both instructors were reviewing and integrating appropriate feedback.  
  • Panels of former students: One attendee noted that he had invited a panel of former students to talk about their experiences in the class and what contributed to their success. The credibility of the speakers and the authenticity of the guidance resonated with the current students.  
  • Strategic use of Learning Assistants or Course Assistants: Some instructors in large or introductory courses used Learning Assistants or Course Assistants – undergraduate students successful in the subject area who are trained to provide in-class instructional support – to scale up instructional reach and feedback. These assistants had been particularly crucial in courses that needed more hands-on instructional support, structure, and feedback.    

Many instructors found themselves structuring tasks and activities for students that, pre-pandemic, may not have required direct guidance and direction. Given this need, the importance of student meta-cognition – knowing how to learn something – was raised, which resulted in the following suggestions:       

  • Using learning science data to persuade students: One participant noted that her students were very responsive to research-based arguments. When she offered students evidence-based examples of effective ways to learn (she cited  The Learning Scientists blog as a good source of information), they responded affirmatively to these suggestions. Leveraging learning science research when suggesting better ways to study – retain, recall, and synthesize content – might be one way to help bolster meta-cognition.  
  • Building in self-reflection on effective learning approaches: An attendee recommended integrating opportunities for students to self-reflect on the usefulness of teaching interventions, such as the one-course-meeting-a-week flipped classroom for starting homework. Such reflection on why a certain approach worked (in this case, in-class time dedicated to starting homework with in-person instructional feedback) may help students build (or re-build) their meta-cognitive muscles.  

The conversation turned to tools that could support both targeted in-class instruction and meta-cognition skill development. Brian Cole, Associate Director of the CTEI, said that he had been investigating different technologies that would enable real-time assessment of content comprehension and upvoting of particularly confusing content areas. Melo Yap, the new Sr. Educational Research Consultant at the CTEI, volunteered Kahoot as a tool that could offer such flexibility. 

 A faculty member suggested developing a toolkit with proven meta-cognitive strategies that could be inserted into the Canvas sections of each course. Instructors and students could access this toolkit on-demand and integrate into it their course design for both “just-in-time” support (e.g., before a high-stakes test) and more long-term development. The CTEI offered to collect any already-available guidance to help students learn more effectively in an effort to start collating this information in one place.  

Caroline Egan
Caroline Egan is a Project Manager in the Center for Teaching Excellence and Innovation, supporting instructional training and development for Hopkins faculty, graduate students, post-doctoral fellows, and staff.

Mike Reese
Mike Reese is Associate Dean of the Center for Teaching Excellence and Innovation and associate teaching professor in Sociology.

Image Source: Unsplash