5 Ways Of Using Formative Assessment For Actionable Data

5 Ways Of Using Formative Assessment For Actionable Data
Summary: Much of the focus in assessments is on outcomes: Did students meet learning goals? In an era of Big Data, we can learn much more by quantifying the learning process through increased use of formative assessments: Are students learning – and if so, how? Here are 5 ways of using formative assessment tools to generate more data.

The Formative Assessment Approach: Data-Driven Decisions 

It is common for teachers and students alike to conflate “Judgment” with “Assessment”. But in virtually every other industry, it is becoming conventional for Best Practices to be equated with Data or Evidence-Based Practices. When President Obama created the Office of Data Science in the White House, he signaled that data science has reached a critical mass, and that more data is the key to better policy, practice, and progress. It isn’t about vindicating partisan perspectives, but divining truth and wisdom from every available resource. Education, similarly, needs pedagogy to have a more robust pool of data to inform development. eLearning in general –and formative assessment in particular– provides the perfect platform to bring Big Data and the associated analytics opportunities into the instructional realm.

The key to making the best use of analytics data is to treat assessments as opportunities: To learn more about ourselves, to understand our learning and teaching processes, to identify areas for improvement, and to build more bridges of understand to assist future teachers and learners in their journeys.

Formative Assessment

In short, formative assessment examines the construction of knowledge and understanding during the learning process; think of it as present tense. Summative assessment looks more holistically at outcomes, after a period of instruction and learning; think of it as past tense. Most well-known exams, like the SAT or even the end-of-year exams administered by the states, tend to fall strongly into the summative side of assessment.

Much more data can be generated by utilizing formative assessment tools during the learning process than by looking at outcomes in the form of summative assessments delivered at the end of lessons. As data scientists are learning in industries from healthcare to manufacturing, more data means more improvement. These are just some of the ways instructors and students can benefit from having more data generated through formative assessment tools:

  1. Real-time snapshots.
    Integrating more formative assessment tools –knowledge-mapping, feedback, self-assessment, goals-checking– enables instructors to drill down more precisely into their instructional methods. At this level, it is easier to identify tools and techniques that correspond with greater student success/satisfaction, and better align courses around what works best for the content itself. Real-time data also enables instructor interventions whenever it becomes clear that a gap of understanding is emerging around a topic, or that a particular cohort of students is missing a foundational concept or piece of training.
  2. Refine curricula.
    Honing in on concepts, lessons, or whole topics that routinely produce low student learning outcomes, assessment results, and self-evaluations is an opportunity to retool the curriculum. Spending more time on trouble topics, diversifying engagement opportunities (more hands-on time, more discussion, more visual aids), and soliciting more feedback are all enabled through a quantified look at formative roadblocks. While summative assessments are concerned with tracking whether students meet broader goals, analysis of formative measures can help inform those goals in advance, giving students and instructors alike a better chance of preparing to meet them later on.
  3. Isolate instructor handicaps.
    Correlating student performance data against other identifying information –age, race, language, professional background– can help better identify instructor areas for improvement. Much is made of the cultural bias inherent in certain assessments like the SAT, or in high school history textbooks. Soliciting student feedback in real-time, as well as matching outcomes data with these kind of personal data can help highlight where instructors can adjust their methods, tools, and content to better serve a more diverse cohort; likewise, it can even help instructional designers pin down subjects and assessments that fail to align.
  4. Poor test-takers.
    Summative assessments overwhelmingly tend to be discrete tests: They are presented as gatekeepers to advancement, further instruction, and academic success. All too often, they don’t remotely resemble the actual learning process. As such, discrete tests are often obvious, intimidating, and unrepresentative of actual student knowledge and goal completion. Surveying students through a variety of formative assessment tools can help instructors identify and accommodate students who may be competent learners, but poor test-takers. At a population level, it can also help identify assessment bias or limitations, and enable instructors to augment their assessments or find alternative means to measure outcomes.
  5. Improve engagement.
    Formative assessment programs can easily integrate into existing instructional methods. Engagement is critical to student success, part of the reason gamification, interactivity, and other hands-on learning activities are gaining so much ground today, and at every level of academia, from the K12 sector to progressive collegiate institutions. Not only does the introduction of learning games help improve student involvement and interest, it provides ready-made snapshots of progress and evaluation without the stresses of more traditional assessment.

Bringing a quantitative element into the process to enable big data analytics to measure instruction, retention, development, and generally bring a best-practices element right into the learning environment in real time; much more robust than end of year exams.