This is the final segment in a three-part series summarizing conclusions and insights from research of active, blended, and adaptive learning strategies. Part one covered active learning, part two focused on blended learning, and today’s article discusses research assessing the value of adaptive learning.

Diverse Definitions

Five young people studying with laptop and tablet computers on white desk.

The University of Maryland writes that “Adaptive learning is an educational method which uses computers as interactive teaching devices” that allocate resources according to the needs of each learner. Educause Learning Initiative describes adaptive learning as systems that “use a data-driven…approach to instruction.” Wikipedia’s definition focuses on technology as the distinguishing characteristic.  Smart Sparrow, an adaptive learning platform vendor, emphasizes the learning experience, noting that adaptive learning “address the unique needs of an individual through just-in-time feedback, pathways, and resources (rather than providing a one-size-fits-all learning experience).” And though each of these is accurate and helpful, they fail to inspire a vision for the true value and benefits of adaptive learning.

What’s special about adaptive learning? Why should you consider using it? One answer is succinctly summarized by Dale Johnson, manager of the Adaptive General Education Program for EdPlus at Arizona State University, who said, “The traditional approach of presenting the same lesson to all students at the same time is being replaced by the adaptive model of delivering the right lesson to the right student at the right time.” Johnson cuts to the heart of the matter; focusing on the value and benefits of adaptive learning rather than describing the technologies that make it work. For today’s blog post, that’s the more relevant framework for our discussion.

Game Changer

Although adaptive learning can be successfully implemented in any discipline, this article cites research from STEM (science, technology, engineering, and mathematics) disciplines. The classic, one-size-fits-all lecture model is commonly used in STEM courses. Historically, those classes tend to have the highest rates of attrition and failure. As a result, educators are looking for ways to increase student success and reduce failure and withdraw rates. Many have turned to adaptive learning as that solution.

Adaptive learning uses specialized computer programs to create a customized, student-centered learning path (Kerr, 2016). These systems establish a baseline of knowledge that estimates the student’s degree of mastery for a topic. As the student progresses and gives new information to the adaptive learning platform, it re-evaluates the student’s proficiency and knowledge (Scalise, Bernbaum, & Timms, 2007) and comes to “know” the student, customizing and adjusting the feedback, practice questions, and support materials to match that student’s skills. Although all students ultimately arrive at the same learning destination, the path traveled by an individual might differ from that of classmates, depending on prior knowledge, learning style, and other factors (Canfield, 2001).

Course Design and Instructor Approach

Effective use of adaptive learning requires a well-designed, pedagogically-sound course structure. Adaptive learning may fail if technology is simply added as an extra element or after-thought. To fulfill the promise of adaptive learning, it must be aligned with the learning outcomes, topics, activities, and organization of the course (Scalise, Bernbaum, & Timms, 2007).

When adaptive learning is used as part of a well-structured course design (or redesign), it harmonizes with the benefits of active and blended learning, to deliver powerful, personalized guidance and support.

Instructors will want to re-evaluate course design and activities from the ground up to ensure successful adoption of adaptive learning. This includes discipline-specific choices as well as non-academic influences such as motivation, time management, psychological and social aspects, emotions, learning abilities, and fostering an inclusive environment. These added elements play a key role in the successful implementation of adaptive learning (Martinez, 2001).

Does Adaptive Learning Work?

Yes! There is substantial evidence to conclude that adaptive learning improves student success.

A study in an introductory chemistry class compared post-test results of two student groups. The group using adaptive learning out-performed the control group by an average of nearly 21% (Scalise, Bernbaum, and Timms, 2007). Research from a basic algebra class noted higher final grade averages with adaptive technologies (Stillson & Alsup, 2003). And another study from college algebra showed that students using adaptive learning scored higher than the control group on pre- and post-test assessments (Hagerty and Smith, 2005).

Here at OSU, several undergraduate courses, including college algebra and introduction to statistics, have reported improved results after redesigning courses to include adaptive learning software.

Benefits to Students and Instructors

Students

Research indicates that under-achieving students gain the most from adaptive learning. But this customized approach improves study habits and attitudes for all learners (Walkington, 2013). Students report feeling like they could succeed in the topic, many for the first time, because of the added support provided through adaptive learning (Canfield, 2001). A research study reported that 61% of students said they learned more mathematics than in previous traditional math classes (Stillson and Alsup, 2003).

Students report benefits in exit surveys from courses using adaptive learning:

  • Able to work at their own pace, using adaptive content as an extension of course materials, concepts, and activities (Stillson & Alsup, 2003).
  • Learned more with adaptive learning (Canfield, 2001).
  • Liked the support of step-by-step explanations, immediate feedback, and customized practice problems (Canfield, 2001; Stillson & Alsup, 2003).
  • Motivated to strive for completion when viewing graphical charts showing progress (Canfield, 2001).
  • Developed better study skills and were willing to devote time to learn, recognizing that these investments brought the rewards of a deeper understanding of course content and, ultimately, a passing grade (Stillson & Alsup, 2003).
  • Less stress and worry because of the self-paced, just-in-time nature of adaptive learning, where new topics or practice problems are only presented when the student is ready for them (Canfield, 2001).

Most students said they would take another class using adaptive learning and would recommend the adaptive format to others (Canfield, 2001).

Instructors

Since adaptive learning uses sophisticated technology, most platforms generate reports and data that inform instructors about individual student performance, including details about the skills achieved, remaining progress to achieve mastery, problem areas, and other critical information. At a glance, instructors can use these vital metrics to monitor student performance and, as needed, intervene and provide additional guidance (Scalise, Bernbaum, & Timms, 2007).

If Adaptive Learning is so Great, Why Isn’t Everyone Using It?

As with any technology, adaptive learning is not a panacea. It has drawbacks and may not be well-suited for every student or every situation.

Those lacking adequate internet speed or easy access may be frustrated. Learners who do not own computers may have difficulty finding systems in campus labs or libraries. Students with minimal prior knowledge may spend more time reaching baseline skill levels than classmates. Those who are employed, have extensive family obligations, or juggle other responsibilities may have challenges effectively managing their time to complete the adaptive learning segments (Canfield, 2001; Stillson & Alsup, 2003).

Administrators and teachers uncertain about how to incorporate adaptive learning may have challenges. When not well-integrated into course design, adaptive learning can create confusion. Course instruction and activities must align with the learning materials delivered by the adaptive system. Since adaptive learning is personalized, students may be working in different sections or topics from peers. When lectures or topics don’t match the adaptive content, students perceive this as two classes, with double the work. When course structure lacks cohesion, students might ignore the adaptive support or conclude that it hinders, rather than helps, their ability to study (Stillson & Alsup, 2003).

Finally, adaptive learning is most often used in classes already known to be difficult. The introduction of a new technology could add a layer of confusion and frustration, especially if its been inserted as an add-on component. Courses that haphazardly integrate adaptive learning might even experience an increase in drops or failures due to poor design. Students less confident using technology might be worried about learning this way (Stillson & Alsup, 2003).

In Summary

Adaptive learning has the potential to increase learning, especially in STEM disciplines. The ability to customize material and content to fit the needs of individual learners is a powerful shift from the more common one-size-fits-all lectures. Although more research is needed to realize the full scope of benefits of adaptive learning, results indicate that adaptive learning may better support universal and inclusive learning goals (Scalise, Bernbaum, & Timms, 2007). Adaptive learning gives instructors valuable information about student performance, and these technologies help students more easily grasp complex concepts and content. The ability to closely match topics to a student’s readiness and knowledge may increase their willingness and motivation to learn (Canfield, 2001).

What’s Next?

If you are interested in learning more about adaptive learning and whether it might benefit your teaching and success of your students, check out these OSU Ecampus resources:

Susan Fein, Oregon State University Ecampus Instructional Designer

susan.fein@oregonstate.edu | 541-747-3364

References

  • Canfield, W. (2001). ALEKS: A Web-based intelligent tutoring system. Mathematics and Computer Education, 35(2), 152-158.
  • Hagerty, G., & Smith , S. (2005). Using the web-based interactive software ALEKS to enhance college algebra. Mathematics and Computer Education, 39(3), 183.
  • Kerr, P. (2016, January). Adaptive learning. ELT Journal, 70, 88-93.
  • Martinez, M. (2001). Key design considerations for personalized learning on the web. Educational Technology & Society, 4(1), 21.
  • Scalise, K., Bernbaum, D. J., & Timms, M. (2007). Adaptive technology for e-learning: Principles and case studies of an emerging field. Journal of the American Society for Informaton Science and Technology, 58(14), 2295–2309.
  • Stillson, H., & Alsup, J. (2003). Smart ALEKS… or not? Teaching basic algebra using an online interactive learning system. Mathematics and Computer Education, 37(3).
  • Walkington, C. A. (2013). Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes. Journal of Educational Psychology, 105(4), 932–945.

If you’re in need of a few good reads to add to your end-of-summer list, Ecampus Course Development and Training has provided suggestions from our team, along with insights into how these texts have encouraged us to ponder the design of online learning experiences for students and support for our online faculty.

Educated by Tara Westover

reading a book

This book will get you thinking about some of the many obstacles that our students may face on their journey into higher education. This memoir is about a young woman who leaves her fundamentalist family to pursue an education, eventually earning her Ph.D. from Cambridge, and who has to emerge from deep familial assumptions about education-as-brainwashing to chart her own path. As I’ve listened to this book on my commute to and from work (yes, it’s a great audiobook, too!), it has given me an opportunity to think deeply about what it means for students to come from a family that does not place any value on formal education, and what courage and persistence would be required to leap into academia and then find a way to belong there. – Katherine McAlvage

Small Teaching: Everyday Lessons from the Science of Learning by James M. Lang

A small change can go a long way. This book is full of examples and quick tips of how small adjustments in a course can lead to significant benefits. These small adjustments particularly help students who come to a course with misconceptions about how to study and learn. View the bibliographic entry (and get eBook access if you’re affiliated with OSU). – Elisabeth McBrien

An Urgency of Teachers by Morris & Stommel

An Urgency of Teachers is really thought-provoking and challenges many of the assumptions and changes in education. It is a wonderful introduction to critical pedagogy, and I return to it over and over for reminders, suggestions, and to help me to continue being a thoughtful and meaningful educator and designer. – Meghan Naxer

What Video Games Have to Teach Us about Learning and Literacy by James P. Gee

While this book isn’t primarily intended for a higher ed audience, it helps introduce many of the connections between learning in a video game and learning in a classroom environment and how we can improve teaching by observing and adapting what video games do particularly well. – Meghan Naxer

Best Practices for Teaching with Emerging Technologies by Michelle Pacansky-Brock

The author, Michelle Pacansky-Brock, shared her tips for Humanizing Online Learning as the keynote speaker at Ecampus’ recent Faculty Forum event. Learning online can be an isolating experience, and, for many students, disconnection can contribute to feelings of self-doubt that undermine their success. Pacansky-Brock’s book features several technologies that increase students’ social connectedness. If you want some quick insights, review technologies highlighted by chapter at the book’s companion site. – Deborah Mundorf

We hope these titles give you some fresh perspectives as you finalize your fall courses. Happy reading!

Oregon State University has more than 570 hybrid-designated courses. These hybrid (“blended”) courses integrate regularly scheduled on-site classroom meetings with significant online, out-of-classroom components that replace regularly scheduled class meeting time. In this blended learning format, face-to­ face meeting time is generally reduced by 30 to 80% compared to a traditional on-campus course.

Hybrid courses range from large-enrollment general education courses to seminar-style graduate courses. Since 2012 when OSU formally established the hybrid course schedule type, the total enrollment in hybrid courses has exceeded 42,000 students.

OSU Portland Center

Ecampus has recently expanded hybrid course offerings through the new OSU Portland Center, including undergraduate hybrid programs in business, psychology, cybersecurity and human development and family sciences. Portland-based graduate programs include the Master of Arts in Teaching, MBA and graduate certificate in business analytics.

As Susan Fein noted in the previous post, Blended Learning: What Dose the Research Show?, the literature provides a wealth of evidence for the efficacy of hybrid education. But what can instructors who design and teach hybrid courses tell us? Here are some valuable highlights from posts of the most recent Hybrid Faculty Learning Community cohort in the OSU Hybrid Faculty Blog. The members of this cohort were each engaged in the redesign of a more traditional on-campus course into a hybrid course that will be offered during the 2019-20 academic year.

Collaboration: Jillian St. Jacques – Applied Journalism: “Our students are thirsty to work with each other because it is stimulating, plain and simple. . . . They find their own interpersonal relationships incredibly exciting, as they agree, disagree, admire and/or square off with each other in the Arena of the Intellect.”

Creativity: Alina Padilla-Miller – New Media Communications: “Through activities, experiments and use of everyday media, there are a lot of opportunities to fold in the creation process. The process of creating is not only necessary to include in active learning but it’s also incredibly engaging and dare I say it, fun! Whether the class is face-to-face, online or hybrid, incorporating active learning will enrich the course and ultimately the student’s experience with the curriculum. Let the creating begin!”

Excitement: Susan Rodgers – Writing: “This is what’s exciting to me about the hybrid format: instead of simply assigning readings and hoping the students will come in prepared, they’ll do quizzes, discussions, and collaborations before they come to class . . . we can take the conversation very quickly to a deeper and more meaningful level during our f2f time.”

Students working together in class

Flexibility: Dennis Adams – Business: “Students can more easily sort out the variance in their individual ability in this format. Students who require more time and exposure can reread/re-watch the material on their own time.”

Ownership: Michelle Maller – Forestry – “One of the most effective ways for a student to really master a concept is to present/teach that topic to their peers. . . . Creating ways for the students to interact with the content in a way that builds ownership of it can affect the overall learning. A good example of this is to use a discussion board to have each student “teach” their peers about a specific topic covered in that module.”

Roles: Irene Rolston – Anthropology: “Rather than students relying on their ‘sage’ to inform them, we have the ability to transform the classroom from unidirectional communication into multilateral communications between instructor to student and student to student. Approaching this from a hybrid design perspective, using the initial collection and deciphering of data online prior to use in the classroom as, for example, small group discussions, moves the omnipotent sage into the role of facilitator, one who directs the flow of the classroom rather than dominating the stage.”

Skills: Inara Scott – Business : “In a blended classroom, we have a unique opportunity to rethink the structure and content of our courses. . . . Rather than delivering content, we should be thinking about what unique skills we are building in students, and how we can engage them in the process of finding, interpreting, and creating their own content.”

To summarize, intentional hybrid course design and delivery afford opportunities for faculty to create engaging learning experiences that effectively interweave the classroom and online learning environments. This may involve rethinking the roles of the instructors and students, redesigning learning activities and even reconsidering learning outcomes to optimize the teaching-and-learning experience!

What are your perspectives on blended learning? How does this teaching modality compare to fully online or traditional classroom approaches?

Thank you!

This post is the second in a three-part series that summarizes conclusions and insights from research of active, blended, and adaptive learning practices. Part one covered active learning, and today’s article focuses on the value of blended learning.

First Things First

What, exactly, is “blended” learning? Dictionary.com defines it as a “style of education in which students learn via electronic and online media as well as traditional face-to-face learning.” This is a fairly simplistic view, so Clifford Maxwell (2016), on the Blended Learning Universe website, offers a more detailed definition that clarifies three distinct parts:

  1. Any formal education program in which at least part of the learning is delivered online, wherein the student controls some element of time, place, path or pace.
  2. Some portion of the student’s learning occurs in a supervised physical location away from home, such as in a traditional on-campus classroom.
  3. The learning design is structured to ensure that both the online and in-person modalities are connected to provide a cohesive and integrated learning experience.

It’s important to note that a face-to-face class that simply uses an online component as a repository for course materials is not true blended learning. The first element in Maxwell’s definition, where the student independently controls some aspect of learning in the online environment, is key to distinguishing blended learning from the mere addition of technology.

You may also be familiar with other popular terms for blended learning, including hybrid or flipped classroom. Again, the common denominator is that the course design intentionally, and seamlessly, integrates both modalities to achieve the learning outcomes.

Let’s examine what the research says about the benefits of combining asynchronous, student-controlled learning with instructor-driven, face-to-face teaching.

Does Blended Learning Offer Benefits?

Blended Learning Icon

The short answer is yes.

The online component of blended learning can help “level the playing field.” In many face-to-face classes, students may be too shy or reluctant to speak up, ask questions, or offer an alternate idea. A blended environment combines the benefit of giving students time to compose thoughtful comments for an online discussion without the pressure and think-on-your-feet demand of live discourse, while maintaining direct peer engagement and social connections during in-classroom sessions (Hoxie, Stillman, & Chesal, 2014). Blended learning, through its asynchronous component, allows students to engage with materials at their own pace and reflect on their learning when applying new concepts and principles (Margulieux, McCracken, & Catrambone, 2015).

Since well-designed online learning produces equivalent outcomes to in-person classes, lecture and other passive information can be shifted to the online format, freeing up face-to-face class time for active learning, such as peer discussions, team projects, problem-based learning, supporting hands-on labs or walking through simulations (Bowen, Chingos, Lack, & Nygren, 2014). One research study found that combining online activities with in-person sessions also increased students’ motivation to succeed (Sithole, Chiyaka, & McCarthy, 2017).

What Makes Blended Learning So Effective?

Five young people studying with laptop and tablet computers on white desk. Beautiful girls and guys working together wearing casual clothes. Multi-ethnic group smiling.

Nearly all the research reviewed concluded that blended learning affords measurable advantages over exclusively face-to-face or fully online learning (U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, 2009). The combination of technology with well-designed in-person interaction provides fertile ground for student learning. Important behaviors and interactions such as instructor feedback, assignment scaffolding, hands-on activities, reflection, repetition and practice were enhanced, and students also gained advantages in terms of flexibility, time management, and convenience (Margulieux, McCracken, & Catrambone, 2015).

Blended learning tends to benefit disadvantaged or academically underprepared students, groups that typically struggle in fully online courses (Chingosa, Griffiths, Mulhern, and Spies, 2017). Combining technology with in-person teaching helped to mitigate some challenges faced by many students in scientific disciplines, improving persistence and graduation rates. And since blended learning can be supportive for a broader range of students, it may increase retention and persistence for underrepresented groups, such as students of color (Bax, Campbell, Eabron, & Thomson, 2014–15).

Blended learning  benefits instructors, too. When asked about blended learning, most university faculty and instructors believe it to be more effective (Bernard, Borokhovski, Schmid, Tamim, & Abrami, 2014). The technologies used often capture and provide important data analytics, which help instructors more quickly identify under-performing students so they can provide extra support or guidance (McDonald, 2014). Many online tools are interactive, fun and engaging, which encourages student interaction and enhances collaboration (Hoxie, Stillman, & Chesal, 2014). Blended learning is growing in acceptance and often seen as a favorable approach because it synthesizes the advantages of traditional instruction with the flexibility and convenience of online learning (Liu, et al., 2016).

A Leap of Faith

Is blended learning right for your discipline or area of expertise? If you want to give it a try, there are many excellent internet resources available to support your transition.

Though faculty can choose to develop a blended class on their own, Oregon State instructors who develop a hybrid course through Ecampus receive full support and resources, including collaboration with an instructional designer, video creation and media development assistance. The OSU Center for Teaching and Learning offers workshops and guidance for blended, flipped, and hybrid classes. The Blended Learning Universe website, referenced earlier, also provides many resources, including a design guide, to support the transformation of a face-to-face class into a cohesive blended learning experience.

If you are ready to reap the benefits of both online and face-to-face teaching, I urge you to go for it! After all, the research shows that it’s a pretty safe leap.

For those of you already on board with blended learning, let us hear from you! Share your stories of success, lessons learned, do’s and don’ts, and anything else that would contribute to instructors still thinking about giving blended learning a try.

Susan Fein, Oregon State University Ecampus Instructional Designer
susan.fein@oregonstate.edu | 541-747-3364

References

  • Bax, P., Campbell, M., Eabron, T., & Thomson, D. (2014–15). Factors that Impede the Progress, Success, and Persistence to Pursue STEM Education for Henderson State University Students Who Are Enrolled in Honors College and in the McNair Scholars Program. Henderson State University. Arkadelphia: Academic Forum.
  • Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. J Comput High Educ, 26, 87–122.
  • Bowen, W. G., Chingos, M. M., Lack, K. A., & Nygren, T. I. (2014). Interactive learning online at public universities: Evidence from a six-campus randomized trial. Journal of Policy Analysis and Management, 33(1), 94–111.
  • Chingosa, M. M., Griffiths, R. J., Mulhern, C., & Spies, R. R. (2017). Interactive online learning on campus: Comparing students’ outcomes in hybrid and traditional courses in the university system of Maryland. The Journal of Higher Education, 88(2), 210-233.
  • Hoxie, A.-M., Stillman, J., & Chesal, K. (2014). Blended learning in New York City. In A. G. Picciano, & C. R. Graham (Eds.), Blended Learning Research Perspectives (Vol. 2, pp. 327-347). New York: Routledge.
  • Liu, Q., Peng, W., Zhang, F., Hu, R., Li, Y., & Yan, W. (2016). The effectiveness of blended learning in health professions: Systematic review and meta-analysis. Journal of Medical Internet Research, 18(1). doi:10.2196/jmir.4807
  • Maxwell, C. (2016, March 4). What blended learning is – and isn’t. Blog post. Retrieved from Blended Learning Universe.
  • Margulieux, L. E., McCracken, W. M., & Catrambone, R. (2015). Mixing in-class and online learning: Content meta-analysis of outcomes for hybrid, blended, and flipped courses. In O. Lindwall, P. Hakkinen, T. Koschmann, & P. Tchoun (Ed.), Exploring the Material Conditions of Learning: Computer Supported Collaborative Learning (CSCL) Conference (pp. 220-227). Gothenburg, Sweden: The International Society of the Learning Sciences.
  • McDonald, P. L. (2014). Variation in adult learners’ experience of blended learning in higher education. In Blended Learning Research Perspectives (Vol. 2, pp. 238-257). Routledge.
  • Sithole, A., Chiyaka, E. T., & McCarthy, P. (2017). Student attraction, persistence and retention in STEM programs: Successes and continuing challenges. Higher Education Studies, 7(1).
  • U.S. Department of Education, Office of Planning, Evaluation, and Policy Development. (2009). Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies. Washington, D.C.

Image Credits

  • Blended Learning Icon: Innovation Co-Lab Duke Innovation Co-Lab [CC0]
  • Leap of Faith: Photo by Denny Luan on Unsplash
  • School photo created by javi_indy – www.freepik.com
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Are you interested in reading about research in the field of online teaching and learning? Could you use some help in reading and digesting the results of various research reports in the field? Would you like to be able to identify the strengths and weakness of the study reports that you read? If you answered “yes” to one or more of these questions then you might be interested in the  Ecampus Research Unit’s new resource: the Report Reader Checklist.

The Report Reader Checklist includes a comprehensive set of criteria that offers you a guide to evaluate the quality and rigor of study reports. The checklist is intended to provide an overview of the foundational elements that should be included when reporting on the results of a study. You can apply each checklist criterion to a report to see whether that element has been included or not.

Here is an overview of the six areas of the checklist and the criterion in each area:

  1. Context: Does the report describe the larger purpose of the study? Does it explain the history or theoretical framework? Does the report include research goals and suggestions for further research?
  2. Methodology: Does the report have a methodology section? Is it clear how data were collected and analyzed? If the study used statistics, were they named? If coding was used, was the procedure described?
  3. Sample: Are the study participants described in detail? Is it clear how participants were recruited? Does the sample represent an appropriate level of diversity? Are subgroups appropriately identified?
  4. Reporting Results: Are all numbers in the report easy to comprehend? Is the “N” provided? Does the report identify missing data? Is it clear where study findings fit with the study’s purpose? Do data visualizations enhance your understanding of the results?
  5. Transparency: Are raw data included in the report? Are instruments or study protocols provided in the report? Are the authors clear about any conflicts of interest? Is the discussion rooted in data results?
  6. Reader Experience: Does the report use language that is easy to understand? Is the report ADA accessible? Does it include a summary or abstract? Is the study an appropriate length?

There are no “points” or “weighting” within the checklist, but if you find one area (e.g., “Context” or “Methodology”) that is missing several criteria within a report, that would indicate that a report is weaker in that particular area.

You can download a one-page PDF of the checklist or visit our supplementary website that provides more details on each of the criterion. Further, the site includes sample reports for each criterion so that you can learn more about areas that you are unfamiliar with.

We hope you find this resource useful for reading and evaluating reports in the field. We also hope it helps you make data-driven decisions for your work.

About the Oregon State University Ecampus Research Unit: The Oregon State University Ecampus Research Unit makes research actionable through the creation of evidence-based resources related to effective online teaching, learning and program administration. The OSU Ecampus Research Unit is part of Oregon State Ecampus, the university’s top-ranked online education provider. Learn more at ecampus.oregonstate.edu/research.

 

Dog running through water with a stick
Image by Wolfgang Horvath from Pixabay.

My interest in learning about motivation in education began many years ago when I started learning about motivation in game design. In a way, while this blog post will follow a different format, it is an outgrowth of my previous post on how game design can influence course design. In order to better understand motivation, in a classroom, while playing a game, and in an online learning environment, I am turning to the body of research that has grown from Edward Deci and Richard Ryan’s Self-Determination Theory (SDT).

What is Self-Determination Theory?

Deci and Ryan’s theory stems from the larger investigation of human needs for well-being. While physiological needs like food, water, and shelter may be obvious, what are our psychological needs? SDT posits that the three basic psychological needs of humans are autonomy, competence, and relatedness. “Like physical needs, these needs are said to be objective phenomena in that their deprivation or satisfaction has clear and measurable functional effects, effects that obtain regardless of one’s subjective goals or values” (Deci & Ryan, 2017, p. 10). In addition to the basic needs, each is also associated with a dichotomy of social environments.

  • Autonomy: “the need to self-regulate one’s experiences and actions” (Ryan & Deci, 2017, p. 10). A feeling of autonomy is not simply being able to make choices, but feeling that your actions and behaviors are in alignment with your own values. Being able to independently make your own choices is certainly one way to feel volitional engagement, but not the only way to fulfill the need of autonomy. Social environments vary between autonomy supportive and demanding/controlling. When was the last time you were able to engage with a situation or action wholeheartedly and felt fulfilled?
  • Competence: “[the] need to feel effectance and mastery” (Ryan & Deci, 2017, p. 11). This need is often paired with receiving positive feedback, seeking and overcoming challenges, and following curiosities. This need has received the most research in motivation and psychological studies, especially in education research. Social environments vary between effectance supporting and overly challenging, inconsistent, or being otherwise discouraging. When was the last time you sought a challenge and positively progressed (or achieved) mastery?
  • Relatedness: “[the need to] feel socially connected” (Ryan & Deci, 2017, p. 11). Feeling relatedness isn’t just about feeling cared for or taken care of, it is also about feeling valued in a community and having a sense of belonging. Social environments vary between relationally supportive and impersonal/rejecting. When was the last time you felt a sense of belonging and valued in a community?

These needs are essential for optimal motivation, well-being, and vitality (Ryan & Deci, 2017, p. 11). The research on how SDT promotes more intrinsic motivation is significant, as well as helps empirically establish different types of motivation (autonomy-control, intrinsic-extrinsic, and internally regulated-externally regulated) (Ryan & Deci, 2017, pp. 14–15).

Designing and Teaching with SDT in Mind

If we want our learning spaces (no matter the modality: face-to-face, hybrid, online, etc.) to promote optimal student (and teacher!) motivation and overall well-being, how can we design these spaces to fulfill these three needs?

  • Autonomy: allow students to make meaningful decisions about their learning, which may include students pursuing objectives in an order of their choice, providing students with additional relevant applications and rationales for activities and materials, providing students with opportunities to roleplay or act through a scenario.
  • Competence: balance the challenge/difficulty of a given task with student ability/skill, set clear goals, scaffold materials or activities, have a system for transparently communicating student progress, provide positive feedback.
  • Relatedness: foster an inclusive learning environment, instill a value of learning, design activities and interactions for peers to share and collaborate their knowledge and experience, provide instructor-to-student interaction.

“In fact, classroom climates supporting autonomy, providing high structure [competence support], and conveying relatedness and inclusion foster personal well-being and feelings of connection to one’s school and community” (Ryan & Deci, 2017, p. 18). Many of these goals may already be met in your courses. However, there are actions and elements of design that can negatively impact need satisfaction as well. For example, overly difficult challenges, overwhelming negative feedback, and social comparisons can inhibit a sense of competence. The role of assessments and grading will need to be covered in a follow-up blog post, as these can have both negative and positive impacts depending on how they are implemented and designed.

In summary, striving to create a learning environment that fulfills all three needs of SDT can be positive and rewarding for everyone in the class, including the instructor. While this is only a brief introduction to Self-Determination Theory as a whole, I hope it has inspired you to consider how your courses can be designed with SDT in mind.

References and Resources

Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry 11(4), 227–268.

Ryan, R. M., & Deci, E. L. (2017). Self-Determination Theory: Basic psychological needs in motivation, development, and wellness. New York: Guilford Press.

Ryan, R. M. & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25, 54–67.

Self-Determination Theory. (2019).

  • This website is a treasure-trove of resources on SDT and its application in numerous fields, including education.

What’s An Image’s Value?

Image of postcard with a picture is worth a thousand words written on it.

Have you ever created an online course without using images? No?

That is not surprising as images can convey emotions, ideas, and much more. Their value is often captured in an old adage: A picture is worth a thousand words.

This article will discuss the value of images in online course design and how using visuals to accompany instruction via text or narration might contribute to or detract from an online learning experience. Let’s begin.

Multimedia Learning: Images, Text, and More

Online learning is a modern form of multimedia learning. Richard Mayer (2009) described multimedia learning as that learning that integrates the use of words and pictures. In traditional classrooms these learning resources might be experienced as: 

  • Textbooks:  Text and illustrations.
  • Computer-based lessons: Narration w/animation
  • Face-to-face slide presentations: Graphics and audio.

In online learning multimedia may also include:

  • eBooks: Text and digital images 
  • Video: Text, images, animations, coupled with audio.
  • Interactives: Maps, images, and video.
  • Digital Visual Representations: Virtual worlds and 3D models.
  • Screencasts: Software demos, faculty video feedback, and more.
  • Audio: Enhanced podcasts or narrated lectures.

These two short lists, although not exhaustive, demonstrates the importance of visual elements to multimedia based learning in online courses. There are many reasons why we might include any one of these multimedia learning experiences in an online course. For our purposes we will explore a bit more the instructional value of visuals to online learning.

So, how do words and pictures work together to help shape learning? Given that this is perhaps the most common learning object used in an online course it would seem useful to understand what may be considered this simple interpretation of visual literacy for learning (Aisami, 2015).

Visual Engagement Of A Learning Object

In a recent study of how people acquire knowledge from an instructional web page Ludvik Eger (2018) used eye tracking technology to examine a simple learning object composed of a title (headline), a visual element (i.e., diagram), and a box of written text. With no audio support for the learning object in this study, participants engaged the content via visual engagement alone. Results indicated that the majority of students started their learning process at the headline or the headline and visual element. The box of information, in text form, was the third part of the learning object engaged.

Within this context eye movement analysis indicates a learning process that is dependent upon a consistent visual flow. Purposely connecting the title, visual element and information text of a learning object may best reinforce learning. By doing this the course designer/instructor becomes a sort of cognitive guide either focusing or not-focusing learning via the meaning structure of the various learning object elements. In our case we want to use visual elements to support performance and achievement of learning tasks.

Choosing Visual Elements

In order to explore the choice of visual elements in an online learning experience it is helpful to understand how we process that experience from a cognitive science perspective.

Clark and Mayer (2016) describe that cognitive science suggests knowledge construction is based upon three principles: Dual channels, limited capacity and active processing. Let’s briefly examine what these are.

Dual channels:

People have two channesl of cognitive processing 1) for processing visual/pictorial material and 2) one for auditory/verbal material. See Figure 1.  below.

 

Model of cognitive model of multimedia learning.
Figure 1.: Model of the Cognitive Theory of Multimedia Learning

Limited capacity:

Humans can only process a few bits of pieces of information in each channel at the same time.

Active processing:

Learning occurs as people engage in cognitive processing during learning. This may include attending to relevant material, organizing that material into a coherent structure, and integrating that material with prior knowledge.

Due to the limits on any learner’s processing capability it is paramount that we select visual images that help manage the learning process. Our goal is to limit excessive processing that clutters the learning experience, build visual support for representing the core learning process, and provide visual support that fosters deeper understanding of the learning at hand. What does this mean in practice?

Managing Processing Via Image Use

Making decisions about image selection and use is a key to managing this learning process. Understanding the meaning of images to select is also key and is really a function of literacy in one’s field and visual literacy in general (Kennedy, 2013).

In practice we can use the following guidelines to make decisions about image use in multimedia-based online learning. 

  • Control Visual Elements – Too many images on a web page or slide may force extraneous cognitive processing that does not support the instructional objective. 
  • Select Visual Elements Carefully – Images difficult to discern are likely to negatively impact learning. Think about good visual quality, emotional and intellectual message of the image, information value, and readability.
  • Use Focused Visual Elements – Target selection of visual support to those images that represent the core learning material and/or provide access to deeper understanding of that core content.

Other Image Tips

Emotional Tone: Emotional design elements (e.g., visuals) can play important roles in motivating learners and achievement of learning outcomes (Mayer, 2013).

Interest: Decorative images may boost learner interest but do not contribute to higher performance in testing (Mayer, 2013). Use decorative images prudently so they do not contribute to extraneous learning processing (Pettersson & Avgerinou, 2016).

Challenge: Making image selections that contribute to a degree of confusion may challenge learnings to dive more deeply into core learning. This is a tenuous decision in that challenge in sense making may prove to foster excessive processing.

Access: Images must be presented in a format that is viewable to users to be practical. This involves an understanding of technical features of image formats, download capability, mobile use, and universal design techniques.

Final Thoughts

It is valuable to remember that visuals communicate non verbally. They are most effectively used when carefully selected and paired with text or audio narration. Visuals appeal to the sense of sight. They have different classifications and could be pictures, symbols, signs, maps graphs, diagrams, charts, models, and photographs. Knowing their form, meaning, and application is part of being a visually literate course developer or instructional designer.

Web Resources

References

Aisami, R. S. (2015). Learning Styles and Visual Literacy for Learning and Performance. Procedia – Social and Behavioral Sciences, 176, 538-545. doi:10.1016/j.sbspro.2015.01.508

Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction : Proven guidelines for consumers and designers of multimedia learning. Retrieved from http://ebookcentral.proquest.com

Eger, L. (2018). How people acquire knowledge from a web page: An eye tracking study. Knowledge Management & E-Learning: An International Journal 10(3), 350-366.

Kennedy, B. (2013, November 19). What is visual literacy?. [Video file]. Retrieved from https://www.youtube.com/watch?time_continue=1&v=O39niAzuapc

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

Mayer, R. E. (2014). Incorporating motivation into multimedia learning. Learning and Instruction, 29, 171-173. doi:10.1016/j.learninstruc.2013.04.003

Rune Pettersson & Maria D. Avgerinou (2016) Information design with teaching and learning in mind, Journal of Visual Literacy, 35:4, 253-267, DOI: 10.1080/1051144X.2016.1278341

 

Credit: Embedded image by Kelly Sikkema on Unsplash.com

I pledge that I have acted honorably in completing this assessment.

There are two sides to the story of security of online assessments. On the one side, cheating does exist in online assessments. Examity’s president Michael London summarized five common ways students cheat on online exams:

  1. The old-school try of notes;
  2. The screenshot;
  3. The water break;
  4. The cover-up; and
  5. The big listen through devices such as Bluetooth headset (London, 2017).

Newton (2015) even reported the disturbing fact that “cheating in online classes is now big business”. On the other side, academic dishonesty is a problem of long history, both on college campuses and in online courses. The rate of students who admit to cheating at least once in their college careers has held steady at somewhere around 75 percent since the first major survey on cheating in higher education in 1963 (Lang, 2013). Around 2000, Many faculty and students believed it was easier to cheat in online classes (Kennedy, 2000), and about a third of academic leaders perceived online outcomes to be inferior to traditional classes (Allen & Seaman, 2011). However, according to Watson and Sottile (2010) and other comparative studies (Pilgrim & Scanlon, 2018), there is no conclusive evidence that online students are more likely to cheat than face-to-face students. “Online learning is, itself, not necessarily a contributing factor to an increase in academic misconduct (Pilgrim & Scanlon, 2018)”.

Since there are so many ways for students to cheat in online assessments, how can we make online assessments more effective in evaluating students’ learning? Online proctoring is a solution that is easy for instructors but adds a burden of cost to students. Common online proctoring service providers include ProctorU, Examity, Proctorio, Honorlock, to name just a few (Bentley, 2017).

Fortunately, there are other ways to assess online learning without overly concerned with academic dishonesty. Vicky Phillips (n.d.) suggested that authentic assessment makes it extremely difficult to fake or copy one’s homework. The University of Maryland University College has consciously moving away from proctored exams and use scenario-based projects as assessments instead (Lieberman, 2018). James Lang (2013) suggested smaller class sizes will allow instructor to have more instructor-to-students interaction one-on-one and limit cheating to the minimum therefore; Pilgrim and Scanlon (2018) suggest changing assessments to reduce the likelihood of cheating (such as demonstrating problem solving in person or via video, using plagiarism detection software programs like TurnItIn, etc.) , promote and establish a culture of academic integrity (such as honor’s code, integrity pledge), and supporting academic integrity through appropriate policies and processes. Kohnheim-Kalkstein (2006) reports that the use of a classroom honor code has been shown to reduce cheating. Kohnheim-Kalkstein, Stellmack, and Shilkey (2008) report that use of classroom honor code improves rapport between faculty and students, and increases feelings of trust and respect among students. Gurung, Wilhelm and Fitz (2012) suggest that an honor pledge should include formal language, state the specific consequences for cheating, and require a signature. For the honor pledge to be most effective, Shu, Mazar, Gino, Ariely, and Bazerman (2012) suggests including the honor pledge on the first page of an online assessment or online assignment, before students take the assessment or work on the assignment.

Rochester Institute of Technology (2014) ’s Teaching Elements: Assessing Online Students offer a variety of ways to assess students, including discussions, low-stake quizzes, writing assignments (such as muddiest point paper), and individual activities (such as staged assignments for students to receive ongoing feedback), and many other activities.

In summary, there are plenty of ways to design effective formative or summative assessments online that encourage academic honesty, if instructors and course designers are willing to spend the time to try out suggested strategies from literature.

References

Bentley, Kevin. (2017). What to consider when selecting an online exam proctoring service. Inside HigherEd. (June 21, 2017). Retrieved from https://www.insidehighered.com/digital-learning/views/2017/06/21/selecting-online-exam-proctoring-service on February 22, 2019.

Gurung, R. A. R., Wilhelm, T. M., & Filz, T. (2012). Optimizing honor codes for online exam administration. Ethics & Behavior, 22, 158–162.

Konheim-Kalkstein, Y. L. (2006). Use of a classroom honor code in higher education. Journal of Credibility Assessment and Witness Psychology, 7, 169–179.

Konheim-Kalkstein,Y. L., Stellmack, M. A., & Shilkey, M. L. (2008). Comparison of honor code and non-honor code classrooms at a non-honor code university. Journal of College & Character, 9, 1–13.

J.M. Lang. (2013). How college classes encourage cheating. Boston Globe. Retrieved from https://www.bostonglobe.com/ideas/2013/08/03/how-college-classes-encourage-cheating/3Q34x5ysYcplWNA3yO2eLK/story.html on February 21, 2019.

Lieberman, Mark. (2018). Exam proctoring for online students hasn’t yet transformed. Inside Higher Ed (October 10, 2018). Retrieved from https://www.insidehighered.com/digital-learning/article/2018/10/10/online-students-experience-wide-range-proctoring-situations-tech, on February 22, 2019.

Michael London. (2017). 5 Ways to Cheat on Online Exams. Inside Higher Ed (09/20/2017). Retrieved from https://www.insidehighered.com/digital-learning/views/2017/09/20/creative-ways-students-try-cheat-online-exams on February 21, 2019.

Derek Newton. (2015). Cheating in Online Classes is now big business. The Atlantic. Retrieved from https://www.theatlantic.com/education/archive/2015/11/cheating-through-online-courses/413770/ on February 21, 2019.

Vicky Phillips. (n.d.). Big Fat Online Education Myths – students cheat like weasels in Online Classes. GetEducated. Retrieved from https://www.geteducated.com/elearning-education-blog/big-fat-online-education-myths-students-cheat-like-weasels-in-online-classes/ on February 21, 2019.

Chris Pilgrim and Christopher Scanlon. (2018). Don’t assume online students are more likely to cheat. The evidence is murky. Retrieved from https://phys.org/news/2018-07-dont-assume-online-students-evidence.html on February 21, 2019.

Rochester Institute of Technology. (2014). Teaching Elements: Assessing Online Students. Retrieved from https://www.rit.edu/academicaffairs/tls/sites/rit.edu.academicaffairs.tls/files/docs/TE_Online%20Assessmt.pdf on February 21, 2019.

Shu, L. L., Mazar, N., Gino, F., Ariely, D., & Bazerman, M. H. (2012). Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end. PNAS, 109, 15197–15200.

George Watson. And James Sottile. (2010). Cheating in digital age: Do students cheat more in online courses? Online Journal of Distance Learning Administration 13(1). Retrieved from https://www.westga.edu/~distance/ojdla/spring131/watson131.html on February 21, 2019

First, let’s start by considering the characteristics of effective feedback in general. What comes to mind?

sound waves

Perhaps you hear in your head (in the authentically authoritative voice of a past professor) the words timely, frequent, regular, balanced, specific. Perhaps you recall the feedback sandwich–corrective feedback sandwiched between positive feedback. Perhaps you consider rubrics or ample formative feedback to be critical components of effective feedback. You wouldn’t be wrong.

As educators, we understand the main characteristics of effective feedback. But despite this fact, students are often disappointed by the feedback they receive and faculty find the feedback process time consuming, often wondering if the time commitment is worth it. As an instructional designer, I hear from faculty who struggle to get students to pay attention to feedback and make appropriate changes based on feedback. I hear from faculty who struggle to find the time to provide quality feedback, especially in large classes. The struggle is real. I know this because I hear about it all the time.

I’m glad I hear about these concerns. I always want faculty to share their thoughts about what’s working and what’s not working in their classes. About a year or two ago, I also started hearing rave reviews from faculty who decided to try audio feedback in their online courses. They loved it and reported that their students loved it. Naturally, I wanted to know if these reports were outliers or if there’s evidence supporting audio feedback as an effective pedagogical practice.

I started by looking for research on how audio feedback influences student performance, but what I found was research on how students and faculty perceive and experience audio feedback.

What I learned was that, overall, students tend to prefer audio feedback. Faculty perceptions, however, are mixed, especially in terms of the potential for audio feedback to save them time.

While the research was limited and the studies often had contradictory results, there was one consistent takeaway from multiple studies: audio feedback supports social presence, student-faculty connections, and engagement.

While research supports the value of social presence online, audio feedback is not always considered for this purpose. Yet, audio feedback is an excellent opportunity to focus on teaching presence by connecting one-to-one with students.

If you haven’t tried audio feedback in your classes, and you want to, here are some tips to get you started:

  1. Use the Canvas audio tool in Speedgrader. See the “add media comment” section of the Canvas guide to leaving feedback comments. Since this tool is integrated with Canvas, you won’t have to worry about upload and download times for you or your students.
  2. Start slow. You don’t have to jump into the deep end and provide audio comments on all of your students’ assignments. Choose one or two to get started.
  3. Ask your students what they think. Any time you try something new, it’s a good idea to hear from your students. Creating a short survey in your course to solicit student feedback is an excellent way to get informal feedback.
  4. Be flexible. If you have a student with a hearing impairment or another barrier that makes audio feedback a less than optimal option for them, be prepared to provide them with written feedback or another alternative.

Are you ready to try something new? Have you tried using audio feedback in your course? Tell us how it went!

References:

Image by mtmmonline on Pixabay.

Note: This post was based on a presentation given at the STAR Symposium in February 2019. For more information and a full list of references, see the presentation slide deck.

 

What is it?

Image of animator’s face in Character Animator program showing the facial data points used for animation creation.

Facial motion capture (Mo-Cap) is a process that uses a camera to map and track points on the user’s face. Software such as Adobe’sCharacter Animator derive data from the camera to animate cartoon characters in real time. This can greatly reduce the amount of time needed to create an animation and breathes subtle life into the character that would be otherwise difficult to achieve. Character Animator harnesses the power of the webcam to map several parts of the face to the respective parts of the character allowing it to record in real time. This includes your eyebrows, eyes, mouth, and head position. It also intakes audio to change mouth shapes to match what the user is speaking. In addition to the webcam, the user can operate their keyboard to trigger additional movements, effects, and walk motions. All these different aspects combine and give the character a personalized feel.

How does it help?

Image of character being rigged into a puppet showing the mesh and body tags.

Cartoon animations currently do not have a large presence in online learning. This is mostly because they take a long time to create and not everyone has had the resources to create them. Normally, character animation for cartoons requires drawing each frame or using a pose-to-pose process called key framing. With innovative technology such as Character Animator, it greatly reduces the barrier to create cartoon animations for online learning. Each motion of the face records instantly and gives the character life by adding subtle movements to the face and head. The bulk of the work is completed early on to draw, rig, and add triggers to the character, or in this case, the puppet. Once the puppet is set up to record, it is smooth sailing from there. All movements, audio, and facial expressions are recorded in one take; greatly reducing the amount of time for development. However, Character Animator allows you to choose which aspects you want to record, so you can record the eye movements one time, then the eyebrows another time. This is helpful for the perfectionists out there who cannot seem capture it all at once.

How does it work?

To create an animation using Character Animator, there are a handful of stages to complete. The first step is to draw the character in either Photoshop or Illustrator. Next, Character Animator imports the graphics and they are rigged into puppets to prepare for recording. This means the eyes, nose, mouth, etc. are tagged with their respective labels. Also during this time, you can create keyboard triggers. These are animations such as arm movements, walk motions, and more, that the pressing of certain keys on the keyboard triggers the character to perform. After the puppets are prepared, it is time to record. It does not have to be shot perfectly all at once; you can blend the best bits from different recordings into one masterpiece. The last step is to export the character’s recording and composite it into a story using video software such as Premiere Pro or After Effects. Once you achieve the flow of facial Mo-Cap, you can start cranking out animations faster than ever before.

Click Image to View Video

Below is a quick rundown of what it takes to set up a character and how to record it. At the end of the video, there is a sample of multiple characters in one scene.

What does the process look like?

 

Author: Zach Van Stone, Oregon State University Ecampus