Active Learning Strategies in CS


Active Learning is a term that is almost used generically when we discuss educational interventions. McConnell (1996) defined active learning in the computer science classroom as approaches that “…get students involved in activity in the classroom rather than passively listening to a lecture. Kramer and Nicoletti (2023) note in an article discussing the positive impacts of an active learning approach in the mathematics classroom that it also allows students to “work together to solve problems and explain ideas to each other. Active learning is about understanding the “why” behind a subject versus merely trying to memorize it… [However] a vexing challenge in calculus instruction – and across the STEM disciplines – is broad adoption of active learning strategies that work.”

Mahavongtrakul (2019) describes how the jigsaw method was used in an Introduction to Computer Architecture course. Students learn parts of the material in small groups, and then these different groups are mixed so that there is one person that learned each piece in a new group.

In an introductory computer science course, the following active learning activities were piloted  (2020) with positive outcomes:

Linked Lists (“Scavenger Hunt”). Students participate in a “scavenger hunt” around the lab. Students begin with a paper note with a location written on one side and a clue written on the other side. The location represents the contents of the linked list node, and the clue represents the pointer, which gives a hint to where the next note is located. The last note contains the clue “NULL” to specify that it is the end of the list. Afterward, students hold the paper notes and physically simulate different linked list operations, such as inserting a node into the middle of a list and deleting nodes in different positions. The peer mentor then draws out an ArrayList. The participants compare and contrast both list data structures in a wrap-up discussion.

Stacks and Queues (“Serving Pancakes”). The peer mentor begins with a review of terms. Then the class simulates a queue by lining up to be served from a stack of paper “pancakes.” Students are then divided into small groups to discuss and write pseudocode for how objects (student and pancake) would use stack or queue data structures. Additional prompts are presented, such as how to get to the pancake at the bottom of a stack. A discussion compares stacks and queues with other data structures (e.g., arrays and lists).

Recursion (“Russian Dolls”).The peer mentor reviews a math factorial example before moving into an analogy of nested Russian dolls. Students are asked how the total number of dolls could be counted, or how to determine if a doll of a certain color exists within the set. In small groups, students write pseudocode for recursive methods; the peer mentor circulates to answer questions before groups explain their pseudocodes.

Binary Trees (“Storytelling”).The peer mentor explains binary trees and the different ways they can be created, then introduces a storytelling activity. Participants tell a chronological story by numbering sentences, each depicting a story event, and placing them in a binary tree structure; the root node is the “present,” the left node is the “past,” and the right node is the “future.” The activity first creates a balanced binary tree, before participants create an unbalanced binary tree where are there no left nodes, so they can address insertion and traversal.

Program Design (“Let’s Build a Museum”). The aim is to demonstrate how one program can be designed in several different ways using a museum curation analogy. Participants sort through a list of items that may be exhibited in a museum and group them via appropriate exhibits: Individual display pieces are variables; exhibits represent classes; and sub-exhibits (such as “airplanes” within “transportation”) represent inheritance or interfaces. Students work as a whole class, then in smaller groups, and then the peer mentor facilitates a wrap-up discussion.

Mergesort (“Automotive Sorting”). Participants work with a simulation involving numbered toy cars that can change lanes on a multi-lane highway. The peer mentor demonstrates how lane changes can represent the splits and merges in the mergesort algorithm before each student takes control of a car, and the class works together to order the cars on the highway. The class then practices with pseudocode to examine the recursive nature of the algorithm before discussing common mistakes and debugging strategies.

If you would like to discuss ways to integrate more active learning strategies in your classroom, please contact me.

Educause recently released a white paper on the 7 Things You Should Know About Generative AI: 
https://er.educause.edu/articles/2023/12/7-things-you-should-know-about-generative-ai

The white paper is a brief primer that discusses the pros and cons of using generative AI in the classroom, as well as the implications of use for faculty and students

Trying Something New In Your Course

Here are a few ideas to consider when trying something new adapted from Tips for Teachers.

Can I improve something I am already doing? 

Before looking to make wholesale changes to your teaching, based on your reflections, identify practices you already do and look for ways to improve them. This should take less time and effort and give you a platform of success upon which to make further changes in the future. For example:

Instead of several worked examples that you have to whiz through, choose one or two that you have thought carefully about. Spend time going through them. Consider modelling them in silence first, and then using carefully considered self-explanation prompts/questions to give students a better opportunity to understand the process.

How will I know if the idea works? 

How are you going to know if the idea has been a success or not? The more objective the measure, the better. For example:

If you are looking to boost your participation ratio by using tools like (Top Hat or PlayPosit), track the number of times you see responses from all students.

What will I have to stop doing? 

This is the question that gets asked the least, and yet is so important. Trying something new may mean you have to no longer do something else. This plays out in two ways: A new idea in the classroom may mean you have less lesson time to do something else. Is that a sacrifice worth making? Planning a new idea may mean you have less planning time to work on something else. Is that a sacrifice worth making?

Interactive Lecturing

In the book,  Instructional Moves for Powerful Teaching in Higher Education, there is a chapter on the advantages of interactive lectures. The writers note, “a traditional lecture may feel like an effective, efficient means of communicating information, but when instructors use class time to only profess what they know without interruption, this deprives students of opportunities to think critically about that information and meaningfully apply it”.

Interactive lecturing is defined by Elizabeth Barkley and Claire Major in their book of the same name as  “the process of combining engaging presentations with carefully selected active learning methods to achieve intended learning goals.”

The chapter focuses on ways to dedicate class time to repeated practice with skills. For example

  • Providing students with a “Preview of Class” slide, which offers students a snapshot of what to expect during course. (This is an advance organizer)

  • A reflective question that allows students to think about the items mentioned in the preview slide and time to write down what they know about the topic based on their own experiences (Activating prior knowledge).

  • The instructor allows a few students to share their reflections, and where possible, makes connections between their reflections and the required reading. As the lecture continues (over 3 hours) she continues to highlight connections. “Over time, students’ comments become increasingly stitched into the lesson’s tapestry”.

Other considerations shared in the chapter are:

  • Keep lectures brief. Resist the urge to lecture expansively. Few students can sustain interest and attention during them. Opting for shorter lectures—or brief bursts of lecture throughout lessons—can maintain student engagement and help students better access your expertise. You might also consider the benefits of an “unpolished lecture” for the lesson or your discipline.

  • Guide students into lectures. Give students time to arrive at a place of focus. Activate students’ prior knowledge. Center their experiences. Invite students to position themselves within a lecture’s key questions, problems, and concepts. Steps like these can provide helpful scaffolding before a lecture, allowing students to better access new information.

  • Offer students multiple ways to engage…from quiet reflection and small group discussion to a metacognitive exercise. Consider interspersing lectures with a similar level of variety to keep students on their toes and welcome all types of learners into lessons.

  • Exercise transparency with students. Demystify your field—and your teaching practice—by exposing your thought processes and rationales to students. Use lectures to model how experts think through problems in their disciplines. In addition, making clear why a particular assignment holds value for one’s intellectual development can improve student motivation.

  • Try metacognition. Successful students self-regulate and are highly attuned to their thought processes. This helps them to focus during class and persist through challenging content and tasks. Kimberly Tanner recommends explicitly teaching students metacognitive strategies like keeping reflective journals or having students track confusion in their thinking. You might also try modeling metacognitive processes yourself during your lectures.

  • Tell stories that stick. The stories we tell our students can mean the difference in their understanding and retaining a given concept. Humor, when deployed appropriately, can have the same effect Make your stories conversational but concise, as too many details may distract from key points and keep students from seeing their conceptual relevance.

The book is one of many resources connected to the Instructional Moves (IM) website based at Harvard University’s School of Education. The goal of IM is to help you incorporate and refine high-leverage teaching practices tailored to the higher education context. Other features include:

Teaching.Tools and the Active Learning Library

The Teaching.Tools Website has a few resources that may be helpful to you.

The Active Learning Library https://teaching.tools/activities allows you to explore teaching strategies aimed to increase engagement in the classroom. This site allows you to search for activities by filtering based on:

  • Difficulty (for the instructor)

  • Prep Time Required

  • Bloom’s Taxonomy (e.g., remember, apply)

  • Active Learning (e.g., individual engagement, small group engagement)

  • Inclusive Learning (e.g., gives students choices, emphasizes the relevance or value of the material)

  • Whole-Person Learning (e.g., emphasizes student values and emotions, emphasizes metacognitive skills)

  • Formative Feedback

  • Activity Time

  • Class Size

  • Class Modality

The Pedagogical Reading List https://teaching.tools/resources is comprised of a community-generated database of resources for college teaching around topics including Accessibility and UDL

  • Active Learning

  • Assessment

  • Curriculum

  • Diversity, Equity, Inclusion

  • Education Research

  • Educational Technology

  • Experiential Learning

  • Graduate Students

  • Learning Analytics

  • Mental Health

  • Online Teaching

  • Problem/Project-Based Learning

  • Race and Anti-Racism

  • STEM

  • Science of Learning

While the Lesson Planning Tool https://teaching.tools/lessonplanner provides an interactive template for creating college-level class sessions. You can use the tool without an account. You must sign in to save your lesson. Accounts are free.

Pre-Course Survey

One way to improve engagement with your students is to learn more about them. A precourse survey is one way to help develop a connection with your students, and get to know them beyond what is shared in an introduction discussion.

What do you want to know about them?

Diligent student in college with classmates, taking notes of teacher lecture.

A survey can help you conduct a needs assessment about where your students are at in terms of prior knowledge, demographics, mindset, learning preferences, goals, content confidence level, preferred feedback style, and/or access to technology.  Because this takes place “behind the scenes” and is only shared with the instructor, rather than in a public discussion forum, you may be more likely to receive candid responses.

What strategies and skills will students need and/or develop in your course?

These kinds of questions can help students flex metacognitive skills and become more aware of their learning habits. As an instructor, this can help you provide more specific feedback on student work, suggesting similar strategies and stretch goals.

  • Reflection on Strategies: Metacognitive reflection questions ask how students get things done. Do you take marginal notes or highlight as you read? What conditions do you need to do your best work?

  • Planning Ahead: Beyond what has worked for students in the past, you might ask about strategies they will use specifically in this class. What times each week do you have earmarked to work on this course?

  • Setting Goals:You might ask them to review the learning objectives, asking what they will commit to accomplishing. And beyond the learning objectives for the course, are there other skills or competencies they plan to work on in the course? Do they have any suggestions for the instructor about strategies for helping meet those goals?

During the first week of your course

Providing students with an opportunity to quiz themselves not on the course topic but on the course itself–how to get started in the course, how to navigate the course, what the course should help students accomplish, and how the course is structured–can help instructors send fewer emails saying, “It’s in the syllabus!”

Given multiple choice or true/false question types, these kinds of pre-course surveys can be automatically scored. Don’t forget to compose feedback for incorrect responses and allow multiple attempts!

What tools are available?

IU supports the Qualtrics survey tool and Canvas includes a dashboard feature that allows instructors to create a type of quiz called ‘ungraded’ that can be used as a survey. In Canvas, once the survey, or ‘ungraded quiz,’ is published online, students can login to their Canvas course page and participate. IU also has access to Google Forms and Microsoft Teams (Microsoft Forms are Available in the Channel and Chat features) for quick survey and quiz creation.

If you’d like support implementing a pre-course survey or questionnaire in your online class, or in any other aspects of teaching and learning, please contact me at your earliest convenience with your availability.