The Open Edition

Category: Featured Book (Page 3 of 6)

Chapter 3: Interleaving

This post is by Gina Bennett.

FIRST, a short retrieval quiz:

  1. In Chapter One, Lang describes 3 different studies to demonstrate how effectively regular quizzing improves retrieval. Can you name any 2 of the subject areas involved?

  2. Also in Chapter One, Lang suggests that the frequency of quizzing is critical to the success of this technique. How often (as a minimum) does he recommend that quizzes be given?

(answers at the end of this post)
 
Big Idea:   Long term mastery of a series of related topics is fostered by spacing out the learning activities over time, introducing new topics before the previous topic has been mastered and intermixing new skills with previously developed skills.

I picture this as the “2 steps forward, 1 step back” approach.

Theories, Principles, Models, and Tips

Lang begins his discussion of the theory behind interleaving with a study that illustrates the difference between massed and spaced practice. Massed practice is defined as time focused entirely on learning one skill or topic until it is mastered, while spaced practice is pretty much the way it sounds: the learning related to that particular skill or topic is spread out and interspersed with time spent doing other things. Interestingly, some of those “other things” include forgetting what’s just been learned. This sounded counter intuitive to me, but as Lang points out, forgetting forces us to really work at the process of retrieval and more strongly embeds the learning in long term memory. Allowing time between learning sessions like this not only forces us into a cycle of forgetting and retrieval, it also gives our brains time to consolidate the new material. This process leads to what’s referred to as “durable learning” — another great term I picked up from this chapter.

Several of the models for incorporating interleaving sound pretty similar to suggestions for improving retrieval (e.g. frequent quizzing), except that here we see a more pronounced emphasis on the inclusion of quiz questions from material learned in the past. A very nice small teaching tip is to end a lesson by asking students to create a test question based on what they learned that day — & instead of waiting for the final or midterm, ask a couple of those questions a few weeks later. And I like Lang’s suggestions for coaxing students to apply previously acquired skills or knowledge to new contexts — transfer of learning is always an issue and I can certainly appreciate how interleaving will help make that happen.

Concerns, questions, musings

I am so tempted to try to sell an interleaving approach a little harder in my ABE math class because the most profound research results mentioned by Lang (and others) are based on students studying middle school math. However, the [adult] students I know who are working at that level usually do not welcome (or need) more frustration in their lives. That concern about feeling discouraged due to lack of a sense of mastery — that’s a major concern. And the students working in a more advanced ABE math course know full well that this course is “terminal;” consequently they are not keen to struggle more than they need to at something that they will “never use again.” I would be very interested to hear what others familiar with the ABE learner audience think about that.

Not a concern but a confusion: I am a bit mystified by Lang’s description of how to employ interleaving in an online learning environment. I suspect his concept or experience of online courses is different from a lot of the ones we offer here. He refers to the “distribution of deadlines” but in my experience most online courses do this anyway. It seems that many of Lang’s examples so far are largely based on “traditional” students: full-time young people who attend on-campus classes in a semester-based format

FINALLY, an exercise in prediction:

In this chapter, Lang describes how interleaving improves the embedding and retrieval of knowledge. Can you think of some ways in which interleaving might also improve understanding?

Links, other interesting things

  • Nice website from the University of Arizona with lots of supplementary material (e.g. blog posts, explanations, PPT slide deck) about interleaving

  • Learning how to Learn is a free MOOC offered on a regular basis by Coursera. If you are interested in learning science and would appreciate an entertaining and accessible approach, you’ll like this course.

  • Have any of you come across the Pimsleur method of language learning? Dr. Pimsleur was a big fan of spaced practice and he developed a schedule of optimal spacing, a system he called “graduated interval recall.” His scheduling sounds like Lang’s spacing recommendation on steroids.

Answers to the retrieval quiz:

  1. The 3 studies Lang refers to to demonstrate the efficacy of retrieval practice involved students learning Social Studies, Art History, & Chemistry.

  2. Lang states (under subheading “Principles”) quizzes should be given at least once a week (preferably in every class).


Image: “interleaving sign” is CC0 – I drew it myself -gb

 

What strategies are you using? Share your ideas in the online Chapter discussions in Mattermost or join us for the live web conference meetup for Chapter 3 on Friday, September 27th at 11:00am.
See How to Participate.

 

Chapter 2: Predicting

Big Idea: Activities where students make predictions about upcoming content improve their ability to remember and comprehend.

Hmm, Chapter 2: Predicting, in James Lang’s Small Teaching is going to explain how the desire to be right in my guess about an upcoming topic reinforces that content. (Reader thinks to self, turns page…)

The second chapter within the Lang’s section on the acquisition of knowledge takes what might seem like a throw-away moment in a lesson and shows the powerful tool it can become.

The authors explore several studies establishing the effectiveness of prediction or prediction-like activities. Following along on this journey is illustrative of the first argument for prediction activities. Each case awakens long dormant linkages in the minds of we readers, having studied memory theory so long ago.

The current research establishes results for both recall and comprehension. The connected nature of knowledge, as we tuck it away and then drag it out to meet a new nugget, is behind the effect that prediction can have on learning. Making predictions lets us have a mental play-date with a fact before seeing how it interacts with the new kids.

In addition to this support for accepted cognitive process, it’s also argued that prediction activities offer a window into the assessment model of a topic. Not just in a way that offers hints for drill and practice, but that reveals the scope and depth of material selected as important by experts.

Another benefit is the revelation of gaps in the student’s own knowledge. Prediction activities can dispel misplaced confidence in the student’s abilities.

Models for prediction activities

  • Pretesting: provide quick, low/no stakes tests about the material to come. Let the format mirror the eventual assessment.
  • Clicker predictions: (or don’t use clickers – there are many free apps that do it just as well). At key junctions in a lesson, present questions requiring students to use conceptual knowledge.
  • Prediction-exposure-feedback: absent technical support, ask students for responses about material to come, based on their prior or potentially related knowledge. Progress through the lesson and take opportunities to elicit feedback about their original predictions, why were they accurate or off the mark?
  • Closing predictions: end a lesson with a call for predictions about material to be learned in the assigned readings. Take up the predictions at the beginning of each class.

Principles for prediction activities

  • Stay conceptual: let students apply their knowledge about how the world works to your question. Learning can come from the exercise, regardless of the accuracy.
  • Provide fast feedback: don’t let the wrong answer bake for too long. Ideally, provide feedback within the lesson, or at least by the beginning of the next session.
  • Induce reflection: every prediction is an opportunity to explore the assumptions and prior knowledge that supported it. The why of a right or wrong answer can have more use than the answer itself.

Some questions

  1. How might prediction activities be experienced by students without a working model/metaphor for a discipline (a philosophy student starting a chemistry class)?
  2. How might we deal with student perceptions of failure (or fears of exposure) in a lesson where prediction activities are used?
  3. If a student arrives at the correct prediction, but based on a completely erroneous paradigm, how might an educator resolve this?

Chapter 1: Retrieving

Big Idea:  Small frequent low stakes testing improves retrieval and learning

 

Part 1 of Small Teaching focuses on how learners acquire knowledge – how they retrieve understand, and predict information that is foundational to higher order critical thinking skills. As educators, we often focus on the application and synthesis of information without giving attention to how we support learners in building foundational knowledge.

This first chapter takes a closer look at the retrieval process and the importance of actively practicing retrieval through testing or quizzing to improve learning. This is known as the retrieval effect or testing effect.  Answering questions about the learning content results in better retrieval than just re-studying the material. This retrieval practice is where learning happens.

CCO photo by Burak K from pexels.com

Think about learning to drive. Reading about driving isn’t sufficient to master driving; much of the learning happens when you practice driving.

The same principle applies to learners. For example, students spend much of their studying time by reading but little time testing their knowledge. This quizzing can be a powerful tool to enhance learning. Lang suggests that if we want to support students’ ability to retrieve information and optimize learning then we have to help students practice retrieval.  Three key principles guide retrieval practice.

Principles

  1. Frequency Matters
    1. Regular quizzing results in greater improvement than sporadic testing
  2. Align Practice and Assessment
    1. Learners need to practice what they are going to retrieve
  3. Retrieval process requires thinking to be effective
    1. More complex questions helps improve retrieval

Retrieval is easy; Encoding is difficult

Much of the chapter concerns getting information out (retrieval) as opposed to getting information in (encoding).  I diverge slightly from the book’s emphasis on retrieval as a barrier to learning.  Retrieval is easy if information has been encoded in the first place.  

CCO photo by Rachel Hall

I often use the following example with my students based on the work of Richardson (1993). Without looking, draw the opposite side of this Canadian nickel.

Many people can recall that a nickel has an image of a beaver and the words 5 Cents. But what else? Does it have other images or dates? Take a look and see how well you did.  Interestingly, very few people can successfully draw a nickel from memory. Why is that? People encode what they pay attention to and what is important to them. In this case, the fact that a nickel  is worth 5 cents is what is important.  Even though most people have seen the image hundreds if not thousands of times, the image isn’t what is relevant to them and therefore isn’t encoded. You cannot retrieve information that was never there in the first place. This is called encoding failure (see Kellogg, 2016).

The same example applies to learning. Students who do poorly at retrieving information have often never encoded the information. For example, they have read their texts and notes and generalized information but not encoded the types of specific details that are required in higher education. The retrieval practice process suggested by Lang is what helps students to encode the information.  However, students don’t necessary know how to learn which is where the strategies in Small Teaching come into play. The strategies are short and focus on the first and last few minutes of class. Several are adapted from Angelo and Cross’ Classroom Assessment Techniques (1993). These strategies focus on assessment as learning versus assessment of learning. Five to ten minutes of class time can make a significant difference to student learning.

Quick Small Teaching Ideas:

  • Give frequent low stakes quizzes
  • Open classes by asking learners to remind you what was last covered
  • Close classes by asking learners to write down the most important concept or one question they still have
  • Close class with a short quiz or problem
  • Use your syllabus to redirect learners to past content and ask them to recall important points from that topic

Links you may be interested in:

https://www.retrievalpractice.org Retrieval Practice has teaching strategies, evidence-based tips and practice guides.
https://www.learningscientists.org The Learning Scientists is a website by cognitive psychologist with the aim to make learning more accessible to students and educators. Has some downloadable resources.
https://www.cultofpedagogy.com/retrieval-practice/Retrieval practice: The most powerful learning strategy you’re not using

 

What strategies are you using? Share your ideas in the online Chapter discussions in Mattermost or join us for the  live web conference meetup for Chapter One on Friday, September 13th at 11:00am.
See How to Participate.

 

References

Angelo, T.A. and Cross, K.P. (1993). Classroom Assessment Technologies (Second Edition). Classroom Assessment Techniques 2nd edition. San Francisco: Jossey-Bass Publishers.

Kellogg, R. T. (2016). Fundamentals of cognitive psychology, 3rd ed. Thousand Oaks, CA: Sage Publications, Inc.

Richardson, J. (1993). The curious case of coins: Remembering the appearance of familiar objects. The Psychologist: Bulletin of the British Psychological Society, 6, 360-366.

 

Introduction: Small Teaching

What does the title of the book ‘Small Teaching’ make you wonder about? 

Small Teaching is “an approach that seeks to spark positive change in higher education through small but powerful modifications to our course design and teaching strategies”

The book Small Teaching describes little changes to learning environments that result in big shifts in learning.  Author James Lang examines strategies derived from research on learning and higher education, that are applicable to the educational environments, and that he himself has observed or experienced.  These activities take one of three forms:

  •   Brief 5-10 learning activity
  •   One time intervention
  •   Small modifications in the course design or communication

Each chapter introduces a concept from learning science with examples of how it can be applied  in a variety of disciplines, and then guides instructors in creating their own small teaching strategies.

Come and join us in our discussions of this book over the next few weeks! Learn and share what small teaching would look like to you.  #BookClubBC @BCcBookclub

Our Online Book Club is back this Fall with “Small Teaching”

We are pleased to announce the next offering of the BCcampus Online Book Club. This free, open, and online professional learning event starts this Fall on September 9th and finishes on November 15th, 2019.  The book selected is “Small Teaching: Everyday Lessons from the Science of Learning” by James M. Lang.

Following up on lessons learned from the initial offering of the Book Club last year, there will additional support for interaction between participants through two open source tools (Mattermost chat and Big Blue Button web conferencing) offered by the OpenETC.

If you are a new participant, take a look at what we did last year in the Book Club in our reading of “How Learning Works”. If your interest is piqued, we encourage you get ahead with a summer reading of  “Small Teaching”  which should be readily available from your local campus library.  There are nine wonderful and highly knowledgeable facilitators from our post-secondary community that will lead our discussion on each Chapter topic: Peter Arthur, Gina Bennett, Asif Devji, Isabeau Iqbal, Laura MacKay, Sylvia Riessner, Keith Webster and Lucas Wright.

All are welcome who are interested in teaching and learning, sharing ideas and exploring our Book Club as an informal and fun way for us to learn together and meet new people in our community.

If you have any questions, send a note to ltet@bccampus.ca or Leva.lee@bccampus.ca

Subscribe to our blog site and follow us @BCcBookClub  #BookclubBC

 

« Older posts Newer posts »