Remote vs. Online: Principles of learning and instructional improvement amidst a health crisis

Adam Fein
5 min readApr 11, 2020

THE CURRENT GLOBAL HEALTH CRISIS has forced a rapid shift to remote learning for millions of instructors in every corner of the world. Note I specify remote learning, rather than online learning, because, as has been elucidated ad nauseam, the courses our students are suddenly taking online have not had the opportunity to benefit from all the academe has learned about learning design in the online space. At the University of North Texas, in addition to 1,500 Spring 2020 online courses already approved through our Digital Strategy and Innovation Center for Learning Experimentation, Application and Research (CLEAR), there were another 7,700 that our faculty worked tirelessly to convert to a remote modality in a tumultuous two-week period. Looking ahead to Summer 2020 and given that the safety of our students, faculty and staff is paramount, we will continue to teach at a distance.

With recently reimagined perspectives on what we can accomplish in a short timeframe, it now seems as if the month-long time period we have to begin to move remote learning courses closer to optimal online learning is far from an effort in futility. Last Fall, we created Course-In-a-Box (adapted from our work at the

) to assist professors by providing a quick training in aspects of compliance, alignment, and general best practices in online course design along with an accompanying template to get started. This week, in collaboration with our DSI faculty fellows and support from Provost Dr. Evans-Cowley, we pushed the training and course template to all Summer instructors. In the first week, the materials were met with cheers and thanks with hundreds of faculty completing the brief training.

There are numerous practices instructors can quickly implement that can have a significant impact on learning performance in the online space. At the University of North Texas, our recommendations are grounded in empirical research and at times, part of our own efforts to explore innovations in learning science. Below, I’ll cover a multimedia-based formative feedback strategy that we are utilizing with faculty to help foster better learning outcomes during a course offering.

As a precursor to our research on whether or not Quality of Video Production Influences Learning Outcomes and The Effects of Formative Assessments on Students’ Performance in Summative Assessments, we first examined designing and implementing formative multimedia quiz feedback and its potential affects on learning performance. Based on Richard Mayer’s Cognitive theory of multimedia learning (Mayer, 2009 & 2014), we know that we remember about 25% of what we read. When pictures, graphics and/or video are added, knowledge transfer is easier. Our findings were nicely covered in this

Blog by their team, but we’ll take the opportunity here to provide an expanded version.

Some foundational background from Mayer:

Learning is (1) a change (2) in what a learner knows (3) caused by the learner’s experience;

Multimedia learning theory is based on three well-established ideas in cognitive science: (1) dual-channel, (2) limited capacity, and (3) active-learning;

Dual channel simply refers to the fact that humans have separate channels for processing words (verbal) and pictures (visual). These channels interact, but they are two separate cognitive systems in different parts of the brain.

Limited capacity is essentially referring to cognitive load, i.e. the human brain can only process a few things (potentially four or five) at any one time in our active consciousness. Too much information will overload working memory.

Active learning happens when a learner (1) pays attention to the relevant material, (2) is able to mentally organize the material into a coherent structure and (3) relates the material back to relevant prior knowledge.

Since we know that cognitive capacity is limited, multimedia learning can be well utilized to reduce extraneous cognitive processing (less relevant material) and manage essential cognitive processing (build representations of the content) while fostering generative cognitive processing (helping the learner to recognize the material in a way that makes more sense).

To determine learning performance, subjects in the Fall 2015 University of Illinois Microeconomics MOOC were randomly assigned to receive one of four different types of quiz feedback on each of three different course modules. Formative feedback on the assessed material was given for a missed question. Learning performance was measured by the ability to correctly answer a second question on the same topic. The entire study is linked here: Multimedia learning: principles of learning and instructional improvement in Massive, Open, Online Courses (MOOCS)

Findings (Fein, 2017)

  1. Designing assessment feedback to only include summative verification feedback (acknowledgement of only a correct or incorrect answer) does not produce any positive impact on performance and should not be considered a useful treatment for students other than to simply verify their progress.
  2. Utilizing any type of instant elaboration feedback has an immediate impact on student performance. A text narrative providing the student with additional information about the misunderstood subject matter produces better student performance results, up to 3.4 times better, than a student who did not receive any elaboration feedback.
  3. Designing formative quiz feedback to instantly (dynamically) deploy a multimedia video that covers the assessed material has the greatest impact on learning performance. Students who had the opportunity to learn the concept visually through the use of pictures, video and audio performed 5.3 times better than a student who did not receive the formative multimedia feedback.
    **Importantly**, this was true of all learners independent of age, gender, level of education and English-language ability. It was also true across four different types of questions reflecting the first four levels of Bloom’s taxonomy.

Take Away

Creating short, simple videos to improve your courses’ feedback mechanisms are effective in helping diverse sets of learners master a topic!

Fein, A. D. (2017). Multimedia learning: principles of learning and instructional improvement in Massive, Open, Online Courses (MOOCS) (Doctoral dissertation, University of Illinois at Urbana-Champaign).

Mayer, R. E. (2009). Multimedia learning (2nd ed). New York: Cambridge University Press.

Mayer, R. E. (2014). Research-based principles for multimedia learning. Retrieved January 16, 2016, from



Adam Fein

Adam D. Fein (PhD, Illinois) is the VP of Digital Strategy & Innovation at the University of North Texas. His research examines multimedia learning performance.