Innovative Pedagogies: #1 Formative Analytics

This Innovative Pedagogies series is based on the article Innovative Pedagogies of the Future: An Evidence-based Selection that offers “a set of innovative, evidence-based pedagogical approaches that have the potential to guide teaching practitioners and transform learning processes and outcomes.” The past few years have seen rapid adoption in educational technology, and this series offers ideas for changes in the practice of teaching and learning to accompany those technology advancements.

There is a new approach in learning analytics called formative analytics. Formative analytics supports learners “to reflect on what is learned, what can be improved, which goals can be achieved, and how to move forward” (Sharples et al., 2016, p.32). This approach is essentially formative assessment supported by analytics techniques. The idea of formative analytics is to provide data directly back to students about the effectiveness of their learning process. A common example of formative analytics is adaptive learning platforms. Adaptive learning systems use a data-driven approach to adjust the path and pace of learning through feedback to the learner and development of a personalized progression through the material. For example, an adaptive learning platform might provide a summary of information to the learner about the percentage of content they viewed, how long they spent viewing that content, and their level of proficiency on the mastery of sections of that content. This gives the learner data to know where and how to spend their time in the future in order to learn better.

One of the most impactful areas of formative analytics is reporting back to learners information related to self-regulation strategies. Self-regulation strategies are things like goal-setting, self-monitoring, effective use of self-instructions or self-talk, and self-reinforcement. Self-regulated learning is a cyclical process, wherein the student plans for a task, monitors their performance, and then reflects on the outcome. This process helps learners to identify how they approach learning and see the benefits or disadvantages of those approaches. “Students have a range of choices and options when they are learning in blended or online environments as to when, what, how, and with whom to study, with minimal guidance from teachers. Therefore, “appropriate” Self-Regulated Learning (SRL) strategies are needed for achieving individual learning goals” (Hadwin et al., 2011; Trevors et al., 2016). The use of formative analytics can encourage learners to critically reflect upon their learning strategies, and where needed adjust them.

Formative analytics is feedback to assist directing an individual learning process. Assisting a learner to reach his or her goals through “smart” analytics, such as visualizations of potential learning paths or personalized feedback is the purpose of formative analytics. Some institutions are providing analytics dashboards directly to students for this purpose. Data reported back to the learner through analytics or an analytic platform can change the learners approach during the learning process. In the Canvas LMS there are analytics that can be made visible to students by enabling the ‘People’ link through ‘Settings’ (Settings > Navigation > enable People). These analytics are considered formative analytics because their intent is to offer the student a snapshot of their activity and performance in the course in order to increase the student’s awareness which may in turn trigger self-regulation, change, and improvement. Guides are offered with more information about these Canvas analytics.


Engagement is critical to student success which is why formative assessments, often in the form of interactivity, gamification, and other hands-on learning activities are gaining so much ground today at every level of academia. Formative analytics is the natural next step as we add these assessments and create a culture of assessment with the goal of student learning in our institutions.

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