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Work 2A: Educational Practice Analysis

Project Overview

Project Description

In Work 2A, you will analyze an educational practice, or an ensemble of practices, as applied in clearly specified learning contexts. Analyze the scholarly findings about the impact of an innovative learning practice (or the need for research in the case of new or under-investigated practices)—a method, a resource or a technology, for instance. Use theory concepts introduced in this course. We encourage you to use theory concepts defined by members of the group in their published works from this or previous courses with references and links to the published works of the other course participants.

This work could be a reflection practice in which you have been involved, or a new or unfamiliar practice which you would like to explore. If the focus of Work 1 was on concepts and theories, the focus of Work 2A is on empirical cases and rigorously researched evidence of effective practice. If your Work 2A is a follow-on to Work 1, reference and link Work 1. Do not repeat any text—if you want to make the connection for you reviewers or readers, a reference with a link will suffice.

Refer to the Work 2A page on our website for additional details:


View examples of previous students' work in the following community:

• e-Learning Ecologies Case Studies community


Work Requirements

Rubric: Use the ‘Knowledge Process Rubric’ against which others will review your work, and against which you will do your self-review at the completion of your final draft. You will find this rubric at the Rubrics for Peer-Reviewed Works page, and also in CGScholar: Creator => Feedback => Reviews => Rubric.

Word length: at least 2,000 words in the main body of the work (excludes experiential alignment, course alignment, introduduction, conclusion, and references) Word count realistically over 2500

Scholarly Sources: While this is not meant to be a literature review, you should still support your case study with scholarly literature and not only the source that might be the focus of your case study.  At least two of the following sources must be included in your work, in addition to other scholarly sources.  For Work 2A, it is okay if you have used them previously.  Refer to our website for the correct APA 7th edition references.

*See admin update for live links!

Media: Include at least 7 media elements, such as images, diagrams, infographics, tables, embedded videos, (either uploaded into CGScholar, or embedded from other sites), web links, PDFs, datasets, or other digital media. Be sure these are well integrated into your work. Explain or discuss each media item in the text of your work. You should refer to specific points of the video with time codes or the particular aspects of the media object that you want your readers to focus on. Caption each item sourced from the web with a link and be sure to cite all media sources in the references list.

References: Include a References “element” or section with the scholarly articles or books that you have used and referred to in the text, plus any other necessary or relevant references, including websites and media.

Icon for From Floundering to Flourishing in Large Enrollment Classes

From Floundering to Flourishing in Large Enrollment Classes

Facilitating Semi-Automated Learning Communities and Peer-to-Peer Interactions

Alignment to Course Themes

This topic aligns with the course EPSY 408, which spans several theoretical concepts including productive struggle, social cognitivism, and brain developmentalism (or constructivism). As we have learned throughout this course, knowledge is not passed from instructor to student but rather grows organically through interactions between the instructor and student, and between the student and their peers. This course has also several times touched on the significance of technology in education, and this paper proposes the use of technology for automating aspects of the large enrollment class to allow for the formation of learning communities.

Experiential Alignment

In my courses I teach hundreds of students introductory programming. It is a large task which requires varied solutions. As I’ve worked to support productive struggle and peer-based learning, I’ve found ways to utilize technology to automate certain parts of the process to make facilitating such interactions possible at a large scale. Active learning is an important part of my approach to teaching.

Media embedded November 20, 2022

Embedded Media 1: The Active Learning Method, Sprouts, 2020

This paper reflects some of the research I have conducted in one particular large class with changes made between semesters and results observed from anonymous surveys administered to the students. These survey results support the need for change in instructor approaches to teaching large classes, and this paper proposes possible solutions.

Concepts and Theories

Piaget introduces the concept of Constructivism, where students acquire and construct knowledge through socialization and interaction with others and the world around them, rather than by passively receiving knowledge from a more knowledgeable instructor or reading it from a text. (1971)

In the amusing video below, a child humorously demonstrates passive knowledge acquisition by attempting to “scoop” knowledge from a book and place it into their brain.

Media embedded November 20, 2022

Embedded Media 2: South China Morning Post, 2020

While this is clearly not a method of gaining knowledge, it does shed some light on the unnaturalness of the concept of directly receiving knowledge and storing it in one’s brain.

It is known from decades of studying the mind that humans need to be involved in their own learning process in order for it to be successful. (Kalantzis, M. & Cope, B., 2008)

Cooperative, problem-based learning is one (of many) ways for students to be involved in the learning process. Maggi Savin-Baden identifies several components for creative effective settings for cooperative problem-based learning to take place: positive interdependence (all team members are needed for the team to succeed), individual accountability, team interactions, and reflection. (2008)

Savin-Baden goes on to describe four types of teams that can be utilized in problem-based instruction: tutor-guided learning team (where facilitator guides the students through a problem), reflexive team (were the focus is on reflection and analysis and students bring their own experiences), co-operative team (as opposed to competitive, students share a goal), and collaborative learning team (where activities and communication support team members individually). (2008)

The Challenge of Big Classes

Over several semesters of teaching a range of class sizes from 20 to 200, we have observed some important differences from both the perspective of the instructor and the perspective of the student.

From anonymous surveys administered to students in CS 303E, a 200-person introductory computer science course, students have reported several benefits of small classes with corresponding disadvantages of large classes. 84% of respondents said that they got to know their classmates well in smaller classes, while only 15% said the same was true of their large classes.

Graph 1: Large Class Survey, Johns, 2022

There are also a lot of benefits for instructors of small classes, such as more flexibility for impromptu collaboration without much advance planning, and more opportunities for one-to-one interactions between the teacher and the student and personalized feedback. (Weimer, 1987) Students also will naturally form a community of learning and will ask each other for help when they get stuck. These group dynamics make creative problem solving a natural component to small classes that the teacher need only embrace, and result in “improved engagement and motivation to learn.” (Samson, 2015)

In a survey sent to faculty, respondents reported that students of small classes form communities of learning and are likely to get to know the professor well.

One of the biggest challenges we have observed in large classes is that students can easily get lost in the sea of faces, and gaps in learning can go unnoticed, with little opportunity for intervention from the instructor.

Image 1: The Ohio State University Teaching & Learning Resource Center, 2022

In the image above, we can get the sense of the distance felt between the instructor and the learners, and how difficult it would be to have one-to-one conversations with each student. The Ohio State University Teaching & Learning Resource Center recommends minimizing the traditional lecture in large enrollment courses, and breaking up lecture periods with activities such as think-pair-share, mind mapping, quiz-like learning checks. (2022)

Some of the large class challenges can be solved through automation – autograders can make grading quicker, lectures can be pre recorded, and Learning Management Systems generally support CSV files for managing groups. There are some setbacks though – autograders limit creativity in assignments, students can’t ask questions during pre-recorded lectures, and premade groups don’t account for students who want to work together.

One of the biggest hurdles we have faced is how to integrate productive struggle into large classes. When we are scaffolding learning content, we want to ensure we challenge students to think creatively and solve problems, and this is often most effective when they struggle together within a learning community. These communities unfortunately do not form naturally in large classes – many students are content to operate in solitude, waiting for direct instruction before moving forward, and many instructors are content to fall back to didactic pedagogy in the large class.

According to the survey results, 100% of respondents said that their typical experience with large classes was that the instructor lectures while students take notes. Only 37% noted that instructors give demos for students to follow along, 21% reported working collaboratively with classmates on large projects, and a mere 16% said the large classes engaged students in active learning with in-class problem-solving or discussion.

Intervention: How to create meaningful learning communities in large classes?

This semester we explored the impact of breaking a large class into mini communities, or cohorts, and ensuring they always interact with the same small group of students throughout the semester so they can get to know each other and feel comfortable solving problems together. Some tasks require smaller groups, so they break into subsets of their communities.

This class is taught online, so these learning communities were facilitated using premade Zoom breakout rooms paired with group discussion boards on Canvas (our Learning Management System). They get to talk to each other while solving small Learning Check problems during each class, and then they post their solutions to the discussion board and peer grade the solutions by replying to each other with feedback. These are 25-person groups which were created at the start of the semester, and they are always with the same group.

By making a CSV file for the groups using Excel, we are able to quickly integrate the groups both on Canvas and using Zoom’s premade breakout rooms, though unfortunately Zoom and Canvas require the CSV file to be formatted slightly differently, but it is still significantly more efficient than creating the groups manually, especially since some class periods they work in smaller subgroups.

Image 2: Johns, 2022

Premade groups make the process more efficient, but what about when students want to work with their friends? For this there is an initial period where teams can make a request to work together using a Google form, and then these groups are created manually, and then the remaining students are randomized into groups. This semi-automated approach gives students autonomy to choose a group or be randomly assigned, so it reduces the instructor workload while still giving students flexibility.

When students are in these smaller groups, they are spending the full class period working together on a “challenge” (a larger problem to be solved as a group). With 200 students working in groups of 2-4, that means roughly 60 breakout rooms on Zoom. During the class period, many groups are bound to have questions or need help with something they can’t quite solve on their own. I have a team of 8 TAs, but the logistics are still challenging.

It is helpful to have a group chat outside of Zoom, in this case using a platform called Discord, for coordinating which breakout room TAs should go to. In the first pass, students would request help through Zoom and the instructor would message TAs what room to go to. In subsequent attempts, we empower the students to use the group chat themselves to directly ask for TA assistance in their breakout room, further automating the process and reducing direct instructor involvement in the process (apart from writing and structuring the activity).

Image 3: Johns, 2022

Beyond just the challenge days, being able to manage student questions is a big task in a big class, and it’s important for students to be able to ask questions outside of class time and preferably without emailing the instructor. We use a help forum called Piazza which allows all TAs to answer questions, and also students can choose to make a post public and other students can answer. This asynchronous forum further solidifies our learning community and the benefits of peer-to-peer interaction via students answering each other's questions.


From the survey, 37% of respondents reported experiencing a class of 500 or more students, and only 21% reported that their largest class was 200 (with the remaining reporting that their largest classes were between 250 and 500). This indicates that the large enrollment class is a common experience for students in higher education.

Graph 2: Large Class Survey, Johns, 2022

58% of respondents said they prefer class sizes of 25-27, and 32% said they prefer classes smaller than 25.

Graph 3: Large Class Survey, Johns, 2022

When asked why they preferred these sizes, students responded with comments such as “I get to connect more with my peers and it’s easier to make new friends” and “Smaller class allows students to engage more and make closer connection with professor and peers.”

When asked about the effectiveness of the Active Learning approaches taken with this course, students responded with overall positive reactions towards the intervention, with 53% saying it was very positive.

Graph 4: Large Class Survey, Johns, 2022


Evidence and Application

Beyond the observations of this study, there have been other studies on active learning in large classes and the benefits to student learning.

In their paper “Using scaffolded feedforward and peer feedback to improve problem-based learning in large classes” Rodríguez et al discuss the results of using an automated system, peer feedback, and a feedforward technique in the contexts of a large class. (2022) In this study, 155 students participated during a 16 week finance course. An automated text summarization tool was used to inform a feedforward session where the instructor addressed general gaps in knowledge that were revealed by the tool. Students were then given anonymous personalized peer feedback on their own work from others in the class.

Graph 5: Rodríguez, 2022

The students in this class also took part in hands-on activities solving problems related to the material being covered. The result of this study concluded that these approaches “had a positive effect on both problem-solving with open-ended problems, as well as on the development of critical thinking skills; especially inference. This is particularly relevant as solving open-ended problems in large classes can be difficult to implement due to the logistics that are involved.” (Rodríguez, N., Yunis, L., Reyes, T., Alvares, D., Joublan, J., & Navarrete, P. 2022)

On Managing Student Work

Large classes also present logistical challenges with managing student work, particularly for instructors who avoid extremely rigid deadlines. Trying to offer flexibility with large classes can result in an endlessly moving line of when all submissions will be turned in, which is problematic for an instructor who wants to post grades and release solutions within a reasonable time frame.

The solution explored in CS 303E was to offer bonus points for submissions turned in 48 hours early, and a 24-hour extension available using a form to make the request. Many students now start early in the hopes of getting the extra credit, and even if they don’t get it by the early deadline, now they have 3 extra days to get help and get it done.

While this may not seem directly related to the learning community, what is really fantastic about this approach is that during those three days the help forum became very active with students both asking for, and offering, help. Anecdotally, this feels like a far more positive community than when all students would post (or email the instructor) in a panic just hours or minutes before a deadline. By spreading out the work it gives much more opportunity for students to respond to each other and form a supportive community.

Future Innovation

The approaches used this semester have improved the flow of class, the feeling of community, and reduced the amount of labor required to organize and manage the process, but there is still more work to be done.

One limiting factor in the success of these approaches has been the reliance on a team of TAs. The number (and enthusiasm) of TAs can vary by semester, and there is also a risk of having TAs unable or unwilling to attend the scheduled class sessions (which the institution does not require them to do, though they are paid for the hours if they choose to attend). Given these risk factors, there is a new approach which will be piloted next semester.

Since the students will be in their cohort for the full semester, high achieving students will be invited to apply to be “discussion leads” for their section. A discussion lead would not need any prior knowledge or experience with the subject, and would only need enthusiasm and a willingness to start each conversation, and to ask questions to keep the conversation moving forward.

Image 4: Coleman, 2022

Additionally, many experienced students find their way into this introductory course and have expressed a desire to complete the “challenge” days on their own so as not to be slowed down by a group. Such students will be allowed to complete the activity solo and then serve as a “student helper” during the challenge day to help other groups (thereby reducing the reliance on the TAs during those sessions).

Finally, inspired by the approach taken in EPSY 408, we will introduce “feedback on feedback” where students not only peer-grade the in-class learning checks, but also provide feedback to their reviewers about how helpful the feedback was or if they were still confused after receiving it.

Critiques and Limitations

The difficulties faced in large enrollment classes are not necessarily the same between in-person and online learning. Much of the research in active learning for large classes is based on in-person instruction, and more research is needed into the specifics of online learning and the challenges brought on by the combination of distance and class size.


With the use of a semi-automated approach to speed up processes while still offering flexibility, creativity, and autonomy, the instructor is able to create small learning communities within a large class and offer support for students without creating an unmanageable workload.


Sprouts. (2020, Oct 1). The Active Learning Method [Video]. YouTube.

South China Morning Post. (2020, June 29). Student in China tries to ‘absorb’ knowledge from book using hands [Video]. YouTube.

Savin-Baden. (2008). A practical guide to problem-based learning online Maggi Savin-Baden. Routledge.

Kalantzis, & Cope, B. (2008). New learning : elements of a science of education / Mary Kalantzis and Bill Cope. Cambridge University Press.

Piaget, Jean. 1971. Psychology and Epistemology: Towards a Theory of Knowledge. Harmondsworth UK: Penguin.

Cope, B. & Kalantzis, M. (2019). Education 2.0: Artificial intelligence and the end of the test. Beijing International Review of Education, 1, 528-543.

Cope, B. & Kalantzis, M. (2015). Assessment and pedagogy in the era of machine-mediated learning. In T. Dragonas, K. J. Gergen, S.McNamee , & E. Tseliou (eds.), Education as Social Construction: Contributions to Theory, Research, and Practice (pp. 350-74). Worldshare Books.

Weimer. (1987). Teaching large classes well / Maryellen Gleason Weimer, editor. Jossey-Bass.

Samson. (2015). Fostering Student Engagement: Creative Problem-Solving in Small Group Facilitations. Collected Essays on Learning and Teaching, 8, 153–.

Teaching & Learning Resource Center. (2022). Teaching Large Enrollment Courses. The Ohio State University.

Rodríguez, Nussbaum, M., Yunis, L., Reyes, T., Alvares, D., Joublan, J., & Navarrete, P. (2022). Using scaffolded feedforward and peer feedback to improve problem-based learning in large classes. Computers and Education, 182, 104446–.

Coleman, D. (2022, March 15). 6 Tips for Facilitating Online Discussions With Students. Campus Press.