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How Do We Achieve Self-Regulated Learning?

Success is in the hand of the student

A young woman wearing a blindfold holding an open book up in front of her face outdoor evening sky behind her

Self regulated learning means students plan, monitor and adjust their own work. See the research phases and practical classroom steps.

In this 2017 article, the second of two parts, Nancy Weinstein sets out three steps for self-regulated learning: set goals, choose strategies, and reflect and adapt. The section below explains what the research literature means by self-regulated learning and what teachers can decide to do with it.

Success is in the hand of the student

In part one of this series we discussed how combining new options for accurate and objective cognitive assessment (attention, memory, processing and reasoning), along with traditional academic achievement data, is the missing piece to enabling self-regulated learning. If we know self-regulated learning is the best way to reach every student and we know we can efficiently get the data to support self-regulated learning, the only question is HOW.

HOW do we do it?

We return to CMU’s Self-Regulated Learning Model. We love this model because it really is so simple. The model that is. Nothing about teaching or learning is simple. However, if we can adopt a structure that is straight-forward to teachers and students alike, the focus can be on learning and not on how to implement another rubric or standard.

As we discussed in Part 1 of this series, the success of this model depends on students being intrinsically motivated to succeed, embracing a growth mindset, and possessing a sufficient self-awareness of their capabilities and needs. Of course, these foundational characteristics are shown to be important to learning across teaching models. However, they are arguably far more critical to self-regulated learning, which depends on students taking the lead in driving the learning process, working independently, and recognizing when and how to ask for help. With a strong foundation in place, the rest is [relatively] easy.

Set goals

There’s no shortage of great materials on effective goal setting, (SMART goals, etc.) so assume those rules apply. However, goal setting with an audience of adolescents does present its own unique set of challenges.

Each student’s goals need to reflect each student’s intrinsic interests. Students need to have a good answer for themselves to the question, “Why am I doing this?” Otherwise, they could easily be distracted by competing interests or have a setback that morphs into a failure. Keep in mind that students might not have the context or foresight to see the bigger picture on their own. They still need their teachers to open their eyes to why the work matters before they can be expected to discover their own meaning.

Let’s not forget that adolescents are at a unique and asynchronous stage in their emotional, social and cognitive development. Some of their needs are developmental while others are more specific to their unique profiles. Consider when a student’s goals should extend beyond his immediate academic performance to include other skills that might be equally important to his lifetime success, such as collaboration, communication and flexible thinking. You’re likely to find that when students expand the scope of their goals, even your highest achievers will find they have clear room to grow. Similarly, those “struggling learners” are likely to discover opportunities where their strengths can shine and their self-confidence can grow.

Choose strategies

It might feel somewhat surprising to know that there is an abundance of evidenced-based strategies that can help students learn more easily, focus more consistently, and remember and recall more efficiently. Teachers and tutors use them all the time. When a student says my teacher “gets me” what he is really saying is that his teacher helps him use the strategies that work best for him so he understands and remembers.

So how do we support teachers to “get” all the learners in their classroom? Objective data on cognitive skills is the game changer. The insight that was heretofore available only through very careful teacher observation (if students were lucky), can now be collected through affordable online cognitive tests. That data enables us to efficiently predict which of the hundreds of strategies would best suit each student, whether he is solving problems in math class, writing an English paper, or working a hands-on project in the shop.

Reflect and adapt

To be fair, it’s not quite that easy. Identifying and effectively using the best-fit strategies takes time, effort and some amount of trial-and-error. Even the best algorithm cannot predict personal preferences, environmental factors, and all the other nuances that go into effective learning. But they can help narrow down the choices to the handful that make the most sense for any given student. Add to that effective teacher coaching and a student who asks for help and is receptive to feedback, and the road to success is reasonably straight-forward.

This is part two of a two-part series.

Self regulated learning in the classroom: what it is and how teachers build it

Self regulated learning describes students who plan their own work, keep track of how it is going and adjust when it is not working. Nancy Weinstein’s three steps above, setting goals, choosing strategies, and reflecting and adapting, follow the same shape as the models that researchers have used for decades. This section places Weinstein’s article in that wider research and describes the evidence in a form a school leader or teacher can use.

What the research literature says

Ernesto Panadero’s 2017 review in Frontiers in Psychology, “A Review of Self-regulated Learning: Six Models and Four Directions for Research”, compares six well-known models, including those of Zimmerman, Boekaerts, Winne and Hadwin, and Pintrich. The review treats self-regulated learning as a framework that covers thinking, motivation, behaviour and emotion. It finds that, although the models use different labels, most fit three phases. In the first, learners analyse the task, set goals, plan and build motivation. In the second, they carry out the task while monitoring progress and controlling their effort and attention. In the third, they judge the outcome, think about what caused it and decide what to change next time.

These three phases line up with Weinstein’s headings. Setting goals belongs to the first phase, choosing and using strategies belongs to the second, and reflecting and adapting belongs to the third. Panadero also notes that the models overlap in many of the processes they describe, which makes it hard to attribute research findings to any single model, and that some models present the phases as a loop that learners repeat rather than a straight line.

Where classroom practice has support

Weinstein writes that students need to ask themselves why the work matters. That fits the first phase, and it also explains why Weinstein says goals should reflect each student’s interests while teachers help students see the larger purpose. For the second and third phases, the U.S. Institute of Education Sciences published a practice guide, Organizing Instruction and Study to Improve Student Learning, in 2007. It lists seven recommendations with ratings for the strength of evidence. Two of them touch directly on self-regulation. The recommendation to help students allocate study time efficiently, which includes teaching students to judge what they have and have not learned, is rated minimal. The recommendation to use quizzing so that students meet key content again is rated strong, and so is the recommendation to ask deep explanatory questions. Spacing learning over time and alternating worked examples with problems students solve themselves are each rated moderate.

The practical reading of that guide is that students can monitor their learning better when they are given regular chances to check it, for example through short low-stakes quizzes and by explaining answers aloud, than when they only reread. Because the guide dates from 2007, teachers should treat the ratings as a starting point and look for newer syntheses for their subject.

A point to weigh in Weinstein’s argument

Weinstein argues that online cognitive tests can predict which of many strategies fits each student. The sources read for this section describe the models of self-regulated learning and a set of general teaching practices. None of them evaluates matching strategies to students through cognitive testing, so a school considering such tests should ask the vendor for independent evidence and should run a small trial with its own students before spending widely. The general practices in the practice guide do not depend on a student profile, and many teachers can begin with them tomorrow.

What teachers and leaders can decide

  • Goals. Ask students to write one goal for a unit in their own words and say why it matters to them, then revisit it at the midpoint.
  • Strategies. Teach two or three study strategies within a subject, such as self-quizzing in science, and let students compare what worked.
  • Reflection. End a task by asking students what they would do the same and what they would change, and give them time to act on the answer.
  • Time. Plan for the teacher’s role as a coach. Weinstein points out that students still need teachers to show them why the work matters before they can find their own meaning.

Self-regulation strategies for students are learned over time, and the same student may need more support in one subject than in another. Leaders who want to build the habit across a school can begin by agreeing on a shared vocabulary for the three phases, so that students hear the same words from every teacher.

Weinstein’s first article in the series, part one, sets out the case for using cognitive data, and the two articles are best read together.

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More on Executive Function

  • Co-founder & CEO of Mindprint Learning,

    Nancy Weinstein is the Co-founder & CEO of Mindprint Learning, an educational technology company specializing in online cognitive assessments and personalized learning that is based in Princeton, NJ. Mindprint has a free, searchable database of over 400 research-based strategies for teachers ready to adopt self-regulated learning. Nancy has an MBA from Harvard Business School and BSE in Bioengineering from the University of Pennsylvania's Management and Technology Program. Prior to Mindprint, Nancy held various roles in technology and finance at Goldman Sachs, The Walt Disney Company, and Bristol-Myers Squibb. She is the mother of two middle school girls.

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