Tag: mastery

Bored, left-behind, or personalized

I have been a supporter of mastery learning since I first read Bloom, Keller, and others in the 1970s. There are many forms of personalization and mastery approaches are but one. Mastery attempts to deal with the issue of individual differences in existing knowledge and rate of learning. Its perspective on learner aptitude argues aptitude should be conceptualized as how long it takes to learn something rather than how much a student can learn in the time provided which is what traditional education requires. For those who could go faster (bored) and those who have been ignored as a class of students move on (left behind), a mastery approach proposes that instruction should address the present situation of each student.


When such ideas were proposed and demonstrated in the ’70s, I would argue that the means to deliver individualized approaches were impractical in most institutions. With technology, the opportunities for practical implementation have changed.

Personalization of student learning has been popularized in recent years. Like so many terms used in education, the meaning of personalization is ambiguous. Personalization could apply to mastery learning, but also to addressing student personal interests. I am an advocate of both concepts. Others are not. For many, student-centered implies student personal interests, but not differences in rate of learning and existing background. I guess the assumption is that somehow differences in learner aptitude and background are being met in traditional classrooms with traditional group-focused approaches. The reality argues otherwise. Many students simply have no realistic chance of dealing with the learning expectations they face.

I just read this commentary on the mastery version of personalization in the New Yorker (https://www.newyorker.com/news/dispatch/the-messy-reality-of-personalized-learning). I also read some of the reactions from pundits who object to the use of technology in this way. I see this as a convoluted problem and I agree with many of the points identified in the New Yorker article. It has beens suggested that “you are doing it wrong” is too often used by tech advocates when addressing complaints about technology. I would use this argument here. If the teacher uses individualized “mastery learning time” to sit at his/her desk and fill out necessary forms or plan lessons for other class sessions, he/she is doing it wrong.

I like to think of mastery approaches as an adaptive textbook presenting content and experiences at the pace suited to the individual. The classroom teacher does not ignore the class just because a traditional textbook is in use and certainly should not ignore students when the computer or laptop is individualizing content and task presentations. The New Yorker article does a nice job of explaining how individualization has become confounded with private schooling and the funding priorities of tech companies. Again, teachers and administrators are not helpless. There are plenty of “free” individualization options available for classroom use (e.g., Kahn Academy) and there is no requirement that schools must take money from Apple, Google, or whatever company happens to be the scapegoat of the moment.

I admit to being frustrated by the lack of individualization in public schools. Your tech integration specialists/coaches/facilitators/etc. should be there to help.

I have written more about mastery approaches elsewhere.

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Salman Kahn at FETC

Salman Kahn was the featured speaker at this year’s Future of Educational Technology Conference. I had hoped that his FETC presentation would be available, but I have not been able to locate it online (I did find this interview). The conference in Orlando was a direct flight from Grand Forks and probably the ed tech conference I found most informative. It was also in late January which was a great time to escape from North Dakota for a few days. I have been following Kahn and his Kahn academy since I first saw his TED presentation. At some point during the process of developing his online resources, Kahn began describing what he was doing as supportive of a mastery approach. I am fairly certain this realization came sometime after his work became popular and I appreciated his association with the mastery learning research that guided my own early thinking about individualization in the 1980s. Too many innovators seem to want to give new names to older concepts. For me, technology provided a practical way to apply mastery concepts in classrooms. The work from the 70s-80s explored the potential of core ideas, but this form of personalization was very difficult for educators to implement. My own thinking about “personalization” assumes there are two issues that should be individualized – a) interests and b) existing knowledge and speed of learning. Neither variable can be addressed with a group-based approach. When the individualization of instruction to address differences in existing knowledge and speed of learning are implemented via a system such as is available through the Kahn Academy, what is happening is unfairly described as students being drilled by a computer. This perception misrepresents how a teacher’s time is intended to be applied. Technology is being applied to individualize information presentation and performance evaluation on an individual basis providing data that allows educators to recognize where their mentorship and tutoring can most usefully be applied. This is a type of interaction that does not happen often enough in most classrooms.

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Personalization for mastery

So, again, and without providing references to the large literature on the topic, I will try to make the case and identify the historical model I think is most relevant to individualization via technology.

My model of instruction (I think it is important to be aware of both models of instruction and models of learning) is most easily communicated using a four-step process identified by scholars Steve Alessi and Stan Trollip. The four steps involve (I have included a couple of additional discriptors I think help with description:

  1. Exposure to information or experiences
  2. Guidance
  3. Extended practice / study
  4. Evaluation / feedback

Following these steps does not guarantee learning, but the steps do identify the various external activities that instructional designers believe offer the most logical and productive approach.

In my thinking, an understanding of these steps must also acknowledge the reality of class and teacher time both of which are limited. For example, one use of technology – the flipped classroom – is an attempt to free up time for steps 2-4 by providing exposure to information through the assignment of instructional video to be viewed outside of class time. Of course, what is assumed is that students will make the commitment to prepare for their interactive time with peers and the teacher.

The mastery model I believe offers the best historical structure for the use of technology is Keller’s PSI (yes, 1968). PSI stands for the personalized system of instruction. Please note Keller focused on how to offer a practical approach to personalization. Keller proposed that presentations were not the most effective or efficient way to expose learners to content (again, the similarity should be obvious). He argued that exposure to information should be based on reading which is a way to describe behavior associated with a technology – the book. He argued that reading provided two advantages over educator presentations. It was personalized in the readers could control the speed at which they would engage with new information. They could reread if they knew they did not understand and this was not really what happened with face to face presentations. In addition, he argued that all readers did not have to be reading the same content at the same time. Why select a common assignment for all when some would understand quickly and some more slowly as a function of background knowledge and aptitude.

Rather than use the technology to avoid human contact, Keller argued that human contact should be provided in a way that concentrated on other aspects of the instructional process. He focused on the use of tutors who would respond to individual questions, administer the assessments, and provide feedback and what some might call remediation. Learners had more and not less time working directly with a more knowledgeable individual.

Mastery strategies as proposed by Keller and Bloom (a more group-based approach to mastery) did kind of fade away. This was not because the research did not demonstrate the value of these strategies, but I believe because it was too complicated for most educators to implement. This is what I think technology changes. Approaches such as the Kahn Academy and I think the approach criticized in the Post article personalize the presentation and the assessment phases of the instructional model. The key is not to eliminate the involvement of the teacher and other more knowledgeable individuals. Use their time to focus on direct involvement with students. In comparison to a textbook, new technologies also provide a specific record of the issues that individual students are struggling with allowing a more efficient focus for teacher assistance.

Should this approach be used in all areas? This would not make sense to me. I think personalization of time to learn offers value on a sliding scale. It is most important when the skills/knowledge being taught are most essential and sequential. Greater existing knowledge is always a benefit to learning, but specific existing knowledge is essential in some areas. Math probably makes the best example. Other skills might be better served by approaches that involve more peer interaction because learning to interact is part of what is to be learned.

Instruction does not have to be inflexible.

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NPR on personalization in Education

NPR just published a post on personalization in education. I encourage your reading of this presentation as it covers some territory I have not seen examined in most current coverage of this topic. The piece begins with a focus on mastery learning which has long been a topic that has interested me. I first published on mastery learning in 1978. The NPR post focuses on the technology-enabled forms of mastery learning using the Kahn Academy as an example and does a reasonable job of explaining what the Kahn Academy makes available to K12 students and the support for this effort by wealthy technology donors.

The article then turns to the critics of Kahn and the idea of understanding personalization as attempting to adjust to differences in the time required to learn. The alternative view of personalization as I would describe what is presented in this article is “learning what you want”. I say “alternative view” as I see these goals on different dimensions rather than as education should be one way or the other. Some might describe my perspective as that of blended learning – educational models exist that personalize both opportunities to learn at different rates (mastery learning) and to explore topics of personal interest (20% time project).

Anyway, in the either/or presentation of the NPR piece, there are several perspectives offered by educational thinkers and classroom educators. Here is a statement provided by one of the educators.

“It works really well, like, the first month,” Finn says. Then, students started to progress at different speeds.

“So I have the kids who are on pace, and I have the kids who are perpetually, always behind. And it got to the point where I had 20 kids in 20 spots.”

This point offered as the source of difficulty in using a mastery approach by a classroom teacher captures the challenge, but also the opportunity of a mastery approach. I would suggest that these 20 kids would be at 20 different spots whether exposed to a mastery approach or not. It is the teacher who would be at one spot in a traditional approach. Student achievement varies greatly and this variability increases year by year. To treat everyone as if they were at the same point limits the opportunities of those who could go faster and frustrates the students who can’t keep up. Worse, moving on when many do not understand or are unable to perform the expected skills often increases the difficulty of these students going forward. The way human motivation works, we tend to give up at some point.

The Kahn approach might come across in the NPR description as 20 kids working in a computer lab for hour after hour. One might ask where is the teacher and what is he/she doing. I have read most things available on Kahn Academy and I would suggest that this is hardly the approach that is encouraged. This environment allows the educator to monitor where different students are at and to recognize precisely which students are stuck trying to deal with a given concept or skill. I suppose the teacher could ignore the student’s plight, but I would think this situation would also allow the teacher to work 1:1 as a tutor. The reality of the 20 student classroom the anti-Kahn educator describes provides limited opportunity for tutoring as educators would be spending their time presenting and assessing.

What I am proposing is that ideas such as mastery learning not be understood in some unnecessarily extreme form. There are variants of mastery approaches applied in many settings and several have been investigated multiple times by researchers. Technology offers opportunities to address several of the challenges that limited the practicality of these previous humans-only implementations. Understanding the role of technology and educator should be the goal not painting a picture that pits one against the other.

I provide a more detailed explanation of mastery learning as part of a different source.

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Kahn Academy Mastery Upgrade

Mastery learning is one of those themes I have returned to throughout my career. It always seemed a great idea, well supported in the research literature, but only made practical by the wide availability of technology. Mastery would be my priority way of thinking about personalization.

I first explored mastery learning supported by technology in the late 1970s. I was a graduate student in the Psychology program at Iowa State and with fellow student Mike Latta we began working with biology professor Warren Dolphin. I had been an undergraduate in biology and was already interested in mastery techniques. I recognized that what Dr. Dophin was doing in his introductory biology course was a version of mastery learning. Yes, this was long before the availability of personal computer-based technology. The large-lecture, introductory course including bi-weekly exams completed on the “fill in the dot” answer sheets scored by computer. The way the exams worked the sequences of questions (1-20, 21-40, 41-60, etc.) corresponded to course units. A student could take an exam over any unit covered to that point with the highest score for each unit counting toward the final course grade. The technology made this system practical as multiple scores with hundreds of students were collected every other week. 

Latta, R. M., Dolphin, W. D., & Grabe, M. (1978). Individual differences model applied to instruction and evaluation of large college classes. Journal of Educational Psychology, 70(6), 960-970. http://dx.doi.org/10.1037/0022-0663.70.6.960

Mastery learning remained a personal interest for more than 50 years and the role technology could play in individualizing learning only expanded beyond the initial focus on making the assessment component easier to implement.

I return to this topic again encouraged by a recent upgrade to the use of Kahn Academy resources as a mastery system. I think I recognized how such systems might be used for a mastery approach before those who design these systems. I first saw Salman Kahn describe his system as useful for mastery learning in his book – One World Schoolhouse. At that time, his way of describing mastery was fairly primitive. Still, I assigned this book in my grad course focused on technology integration and expanded the description in the textbook with my own explanations of what mastery systems are.

If you are unfamiliar with the free Kahn Academy web site or unaware of the basics of a mastery instructional system, I encourage you to take a look at my brief videos on these topics.

The Kahn approach has grown far more sophisticated and makes a great example of the role technology can play in individualization.

The updates to the Kahn approach is described in a recent announcement.

The changes to the Kahn Academy mastery system include:

Learners now reach 100% mastery from unit mastery alone. The Course Challenge no longer accounts for a separate 20% of mastery points.

Course Challenges remain on the site as an option for learners to accelerate their mastery progress, and an efficient way for a learner with lots of prerequisite knowledge to level up in a course.

Learners can now be moved down based on their performance on a practice exercise as well. If someone is at Mastered and gets between 70% and 99% on an exercise, they will move down to Proficient in that skill. If a learner is at Mastered and gets less than 70% correct, they will move down to Familiar. If a learner is at Proficient and gets anything other than a perfect score, they will move down one level to Familiar

The Kahn Academy makes no assumption that the online system will meet the needs of all. The data collected in student efforts and the efficient way of presenting these data to students and teachers allows the teacher to spot those students who are struggling and focus her/his attention more efficiently. 

Kahn offers a sophisticated approach that includes the recognition that the teacher plays an important role and helps the teacher identify those students most in need of her/his assistance. Too often, when technology is used to fulfill part of the need for content presentation, it is assumed that the educator plays no meaningful role. When used appropriately, this assumption could not be further from the truth. 

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A realistic look at the concept of a growth mindset

For a time, educators have been enamored of the growth mindset. Now, it appears that the concept, like so many other educational fads, has limited value. Research show little benefit from promoting the idea with students. 

It is/was an idea educators liked. For me, it was a new term applied to an old idea with a twist (the strange notion that Dweck somehow integrated an old idea with some flawed interpretation of brain plasticity). The brain plasticity thing was promoted as a way to encourage sticking with the effort focused on learning because science tells us you can change the brain through repetition. This is kind of true, but the repetition required to “rewrite” the brain is far more than an extra hour or so of studying.

As parents, coaches, and educators we like to promote the notion of “trying”. When I was a kid, the sportscaster used to sign off his daily show by saying:

A winner never quits and a quitter never wins.

For me, the fixed and growth mindset idea was a simplification of attribution theory. I liked attribution theory better as it seemed more complete. I liked to explain an attribution as an explanation for performance given to others and to the self. This is pretty clear what “to attribute” means. The four categories of attributions were luck, other, ability, and effort. Ability and effort seem similar to fixed and growth. Attribution theorists also noted we attribute success and failures to others and to luck. A considerable body of research exists with something called attribution retraining. Again, the goal was to get the individual to be changed to move toward effort attributions. Note the similarity of encouraging a growth mindset.

One of the issues with this model is that some behaviors are in fact influenced by ability (I prefer aptitude). The reality is that in many competitive life situations some goals will not be met. Some premeds will not be admitted to medical school. Some high school students will not make the 12 player varsity basketball team. Life does force us into accepting an aptitude attribution. When I teach this model, I like to suggest that dealing with accepting a lower aptitude is life’s way of suggesting we should focus on something we are good at. This can be a good thing. What happens to the premed who fails to accept the Cs in calculus and chemistry and persists? What about those of us advising such students? Knowing the odds even with retaking these courses, if a student is really giving his or her best effort, should the student be encouraged to continue to invest time and money.

I tend to think about situations like this as a function of a whether a goal is competitive or not and whether the environment can be changed or not. I don’t think it appropriate to suggest anyone can get into med school or make the varsity team. I do think it appropriate to suggest everyone can learn to read or learn important mathematical skills. This final optimism comes with the commitment to assure that the environment will accommodate the effort that will be required. Encouraging a growth mindset without assuring that sufficient time will be provided is unfair. For some students who struggle to keep up with their classmates this expectation is unfair. This is why I have always been a fan of personalization through mastery learning and why I have been interested in technology as a practical way to make mastery possible.

Without adapting the environment, the growth mindset thing is a label adults use to make themselves feel like they have done something when they have only encouraged certain learners to struggle with an impossible challenge.

 

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Embedded formative evaluation = mastery learning

One of the ways in which I presently see technology improving learning experiences and success involves methods of individualization that allow individuals to move forward at a rate suited to their individual aptitudes and past experiences. My thinking about this opportunity has been shaped by my previous exposure to the theory and research of mastery learning. This perspective, which I associate with Bloom, Keller and other researchers of the late 1960’s and 1970s, provides the rationale for present practice. Many ideas that were great and well-substantiated ideas at that time were difficult to implement. One way I often look at technology now is as a way to take advantage of great ideas in ways that are now practical. The use of history to claim “we tried that and it did not work” needs reexamination. It is important to ask the why question? Sometimes the why is known and ignored. This is the situation in which interesting ideas reemerge in some form based on a similar interesting past ideas, but are a waste of time and energy because the conditions of why have not been acknowledged and/or changed. For me, the argument that learning to code will develop critical thinking falls into this category. Then, there are examples in which the why should encourage a second look if the conditions of the why have changed. I see this as the case with mastery learning.

I had my class this semester read a review by Shute and Rahimi (see citation at the conclusion of this post). This article focused on recent technology-supported instruction that offered data on the importance of competence and feedback. No mention was made of mastery learning. The article used a different vocabulary which I remember as “embedded formative evaluation”. So formative evaluation is likely a familiar concept (Bloom did see his group-based mastery learning as involving formative evaluation). The idea is that technology-enabled systems can incorporate formative evaluation as a mechanism to provide feedback and determine when individuals should progress. If these new words appeal to you, I think this is great and perhaps this appeal may encourage attempts at application. What I think is unfortunate is that a vast collection of work is out there and may allow new innovators to avoid tactics that were unproductive once and will likely be so again unless the circumstances of application are changed.

Shute, V.J. & Rahimi, S. (2017).  Review of computer-based assessment for learning in elementary and secondary education. Journal of Computer Assisted Learning, 33, 1-19.

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