When looking at the name Serverless, it may seem obvious what Serverless is; the lack of a server for an application. The name is actually quite deceiving, as Serverless applications still require servers to perform their duties. Serverless actually refers to a collection of managed cloud services that help to run our applications including storage, databases, functions, back and forth data transfer and more. With serverless, a cloud provider like Amazon Web Services, Google Cloud or Microsoft Azure handle all the configuration, provisioning and management of the server instead of the developer. In simple terms, this means organizations adopting a serverless architecture will be saving a lot of time and money by removing the need to worry about setting up and managing servers.

The Platform Development Team (part of the multimedia group at Oregon State University Ecampus) builds and maintains a number of platforms that leverage Serverless. Web Platforms are pieces of software that facilitate the creation and consumption of content or activities at scale. By using Serverless, our team has experienced a huge decrease in time needed to develop and deploy new platforms and applications. Without the need for our team to configure and manage servers we can handle the setup of our backend for new applications more quickly and efficiently. Any support needed for a dedicated server has also completely disappeared, that is now all handled by the cloud provider. Another huge money saver for our team has been the lack of need for a dedicated server (a server dedicated to you, not shared with anyone else). In the past when using a dedicated server, you would have to pay for both the server, in addition to any resources dedicated to that server, these costs continue to occur even when the server is not in use. With Serverless, you simply pay for what you use, this means when our applications are not receiving requests we are not being charged. When a serverless architecture is performing jobs, the costs accrued are very small, each job costing less than a fraction of a penny. The combination of both an increase in our speed to produce new applications and the lower price tag of using Serverless to handle tasks has allowed our team to undoubtedly save on development costs and provide software to users in a timelier manner.

Apart from its cost benefits, there are also many other positives to using a serverless architecture. These include security, scalability and accessibility. Because the server is no longer managed by the developer, many of the security aspects for applications that a developer would have had to manage in the past are handled by the cloud provider. There are still many security concerns a developer has to consider and handle outside of what the cloud provider handles, but Serverless helps reduce the list of concerns for the developer. Scalability is also a huge plus. As an application gets more popular or starts receiving more requests, Serverless allows scaling to handle those requests. With a dedicated server you would need to manually increase resources. Often when increasing the resources for a dedicated server there will likely be a good portion of those resources going to waste (wasted resources means wasted money), especially as the application receives different levels of traffic at different times. With Serverless, there is no need to worry about wasting resources because it only uses what is needed and scales to the amount of traffic an application is receiving. One of the main goals of our team is to make everything that we develop fully accessible. Serverless helps to us achieve this goal by being offering the ability to deliver content from different regions all over the world, rather than being dependent on a delivering all content from dedicated server located in Oregon. This allows students to more easily access our content and at higher speeds.

Ecampus’ Platform Development Team has seen so many benefits from using the serverless architecture over a dedicated server that it is now used in almost everything that we do. Every single one of our platforms including NES (our platform designed to handle long form content), SLIDE (our platform designed to add interactivity to slideshows), VDL (our platform designed to add interactivity to videos) and the upcoming interactive labs platform all have fully adopted a serverless architecture, which has helped us in producing interactive content for Ecampus’ courses in lightning fast speeds. We can also now utilize the time we have saved to improve our platforms and the overall interactive content that is used in Ecampus’ courses. In summary, Serverless has not only saved our team time and money but also has allowed us to offer better learning experiences to students taking Ecampus’ courses.

Author – David Jansen

Over the last several years, research on online education has been growing rapidly. There has been an increased demand for quality research online teaching and learning. This demand now seems more urgent as teaching modalities are changing due to the COVID-19 pandemic. Since 2016, the Ecampus Research Unit has been funding OSU faculty-led research on online and hybrid education through the Ecampus Research Fellows Program. The goals of the program are the following:

To fund research that is actionable and that impacts students’ learning online;
To provide the resources and support to “seed” pilot research leading to external grant applications;
To promote effective assessment of online learning at the course and program-levels at OSU;
To encourage the development of a robust research pipeline on online teaching and learning at OSU.

Ecampus Research Fellows are funded for one year to engage in an independent research project on a topic related to online teaching and learning. Fellows may apply for up to $20,000 to support their research project. Up to 5 projects are funded each year. The program follows a cohort model in which fellows meet on a quarterly basis as a group to discuss their projects and receive support from the Research Unit. Each fellow completes an Institutional Review Board (IRB)-approved independent research project, and they are required to write a white paper based on their project results. The program’s white papers are published by the Ecampus Research Unit.

Actionable research impacting online education

In the past five years, the program has funded 24 projects with 34 faculty from across the university. The funded research has been conducted in anthropology, biology, chemistry, education, engineering, geography, mathematics, philosophy, physics, psychology public health, rangeland science, sociology, statistics and veterinary medicine. The faculty have benefitted from having dedicated time and resources to undertake these research projects. Their fellows’ projects are significant for their own research pipelines, and their findings are valuable Ecampus as we continue to innovate in our development of online courses. An example is geography instructor, Damien Hommel’s project, which led to a larger effort toward expanding experiential education for Ecampus courses beyond his discipline. Other fellows’ projects are providing valuable information about peer influence, inclusive teaching, hybrid laboratories, video segmentation, online research platforms, and more.

Becoming a research fellow

Are you an OSU faculty member interested in doing research on online education in your discipline? Previous experience with classroom-based or human subjects research is not a requirement. The Ecampus Research Unit is available to support you with your application and the research design process. We will be accepting our 6^th cohort in 2021. The application is available now and is due on November 1^st. Funded projects will be notified by December 1^st.

If you have questions about the program contact Mary Ellen Dello Stritto (maryellen.dellostritto@oregonstate.edu), the director of research for OSU Ecampus. Additionally, attend an information session on Tuesday, September 29, 2020 at 1p.m. or Friday, October 2, 2020 at 11a.m. To register for one of these information sessions email: maryellen.dellostritto@oregonstate.edu.

About the Oregon State University Ecampus Research Unit

The Oregon State University Ecampus Research Unit responds to and forecasts the needs and challenges of the online education field through conducting original research; fostering strategic collaborations; and creating evidence-based resources and tools that contribute 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.

Assignments are an integral component of the educational experience to guide the teaching and learning processes. In fact, Dougherty (2012) contends that assignments are instructional events that aim to teach for learning, that is “recipes for instructional events— lessons in the best sense— and their main function is to create a context for teaching new content and skills and practicing learned ones.” (p. 23). Assignments as instructional plans provide students with the opportunities to apply concepts they studied in the class. Further, through assignments, students can demonstrate the skills developed in a unit of content in more concrete ways and aligned to the goals of the course.

In my consultations with instructors I often hear them raise concerns about course assignments. These concerns range from making assignments more practical and relevant, clarifying the purpose and instructions, integrating problem-solving and critical thinking, to including authentic and experiential tasks. In addition, I hear instructors mention that some assignments that students submit are incomplete, offer superficial and unsubstantiated arguments (i.e., written reports), focus on tangential ideas, have been googled, reflect bias, and are simple opinions using non-credible sources. These concerns are very valid and it is important to examine the assignments deeper. What I have noticed is that some assignment descriptions lack a purpose and clarity. In a word, assignments need to be transparent.

Determining the structure of an assignment bears the questions of how can instructors make the assignments learning events that are clear and relevant enough for students? how can students not only demonstrate what they learn, but also use the assignments as catalysts for further intellectual and academic challenges? Let’s take a closer look at transparency.

Transparency

The first time I heard about transparency in assignment design was at the Wakonse Teaching and Learning conference a few years go. Several sessions and small group activities at the conference showed us that the assignments need to have a clear structure, detailed instructions, and a grading criteria. Obviously! I said to myself at the time. However, the reality is that assignments tend to be reduced to a list of instructions, tasks that students need to complete and submit for a grade. In some cases these instructions vaguely indicate the grading criteria in terms of the format and style (i.e., number of words, font size, spacing).

The underlying framework for transparent assignments is a structure that clearly describes the purpose of the assignment, the instructions or tasks, and the grading criteria (Dougherty, 2012; Winkelmes, 2013; Winkelmes, Bernacki, Butler, Zochowski, Golanics, & Weavil, 2016). Winkelmess and colleagues (2016) draw from three theoretical bases to support the three-stage framework: metacognition, agency, and performance monitoring. Contrastively, Dougherty (2012) draws from instructional strategies informed by backward design and alignment to outcomes to set the assignment structure. In this framework, instructors deliberately design the assignment for high quality learning experience and relevance to students. In their research study, Winkelmess and colleagues (2016) found that students who received transparent assignments showed evidence of greater learning in three areas related to student success: academic confidence, sense of belonging, and mastery of skills.

Designing transparent assignments involve creating a clear and coherent architecture. Through this structure students can think deeper about the concepts studied, focus their attention on particular topics, make connections to real-world contexts, and see the relevance for their future lives and goals (Dougherty, 2012). In doing so, instructors need to create a harmonious structure that clearly explains why students need to do an assignment, what is the assignment about, how to do the assignment, and how they will be graded on it.

When I presented this architecture to one instructor, he replied “you are asking me to tell students the answer! Why would I need to hand-hold students in this way when I want them to be problem-solvers and critical thinkers?” While this comment is valid, and also paralyzed me for a few seconds, I engaged the instructor in discussing what the assignments need to be clear. For instance, we talked about how students will know what to do, why students should care about completing the assignment (besides the grade), and how students will meet the expectations if they don’t know the purpose and the way to complete it. In addition, I said “you want students to be problem-solvers of the content and topics, not problem-solvers of the assignment design.”

A transparent assignment should have the following three basic components: purpose, task, and grading criteria.

Purpose

The starting point in an assignment is to be able to answer the question of why? Why will students learn from this assignment? Why will students need to complete this assignment? Why is this assignment important in students’ learning? Stating the purpose of the assignment serves a two-fold objective. First, it gives the instructor a frame of reference for creating an activity that is relevant and meaningful to students, and that connects to the learning outcomes. Second, the purpose of the assignment gives students a focus and a sense of direction.

Winkelmes (2013) suggests establishing the purpose in terms of the skills students will practice and the knowledge they will gain. In addition, the purpose can also be determined by contextualizing the learning outcomes in practical ways within the activity.

Task

You can call it tasks, details, instructions, steps, or other. In this structure, the instructor describes what students need to do, what resources they can use, and the expectations of the assignments. Having a clear set of instructions makes the assignment more rigorous and helps students produce more high-quality work.

Grading Criteria

Providing the criteria of how the assignment will be graded will also give students a sense of clarity and direction. Clear expectations through a rubric or grading guidelines helps students adhere to the outcomes of the assignment. Winkelmes (2013) suggests including several examples of real-world problems so students can see how the application of knowledge and skills will look like.

Remarks

A transparent assignment should have a well-structured framework or an architecture of steps. Transparency in assignments is a mindset, a way of thinking, the vision that students are given clear and relevant learning events that allow them to demonstrate their learning, and foster their engagement. Transparent assignments can be designed as stand-alone pieces or as a multi-stage assignment. Multi-stage assignments can build on cognitive complexity, include multiple skills, and extend learning to outside the class. In our next blog, I will look at how to design multi-stage assignments.

Sources

Dougherty, E. (2012). Assignments matter: Making the connections that help students meet standards. Alexandria, VA: ASCD.

Winkelmes, M. 2013. “Transparency in Learning and Teaching: Faculty and Students Benefit Directly from a Shared Focus on Learning and Teaching Processes.” NEA Higher Education Advocate, 30(1), 6-9.

Winkelmes, M. A., Bernacki, M., Butler, J., Zochowski, M., Golanics, J., & Weavil, K. H. (2016). A teaching intervention that increases underserved college students’ success. Peer Review, 18(1/2), 31-36.

This is the paradox of failure in games. It can be stated like this:

We generally avoid failure.

We experience failure when playing games.

We seek out games, although we will experience something that we normally avoid. (Juul, p. 2)

As a continuation from my last blog post considering grades and Self-Determination Theory, I wanted to take a brief side-quest into considering what it means to experience failure. Jesper Juul’s The Art of Failure: An Essay on the Pain of Playing Video Games will provide the main outline and material for this post, while I add what lessons we might learn about feedback and course design in online settings.

Dealing with Failure

Juul outlines how games communicate through feedback using the theory of Learned Helplessness. Specifically, he focuses on Weiner’s attribution theory, which has three dimensions:

Internal vs. External Failure
1. Internal: The failure is the fault of the player. “I don’t have the skills to defeat this enemy right now.”
2. External: The failure is the fault of the game. “The camera moved in a way that I couldn’t see or control and resulted in a game over.”
Stable vs. Unstable Failure
1. Stable: The failure will be consistent. No recognition of experience gained or improvement. “No matter what I do, I can’t get past this challenge.”
2. Unstable: The failure is temporary. There is a possibility for future success. “I can improve and try again.”
Global vs. Specific Failure
1. Global: There is a general inability preventing success. “I am not good at playing video games.”
2. Specific: Poor performance does not reflect on our general abilities or intelligence. “I’m not good at flight simulators, but that doesn’t mean I’m bad at all video games.”

In general, a combination of Internal+Stable+Global failure feedback would contribute most strongly toward a player adopting a learned helplessness mindset. There is a potential parallel here with course design: when a student does not do well on an assessment, what kind of feedback are they receiving? In particular, are they receiving signals that there is no opportunity for improvement (stable failure) and that it shows a general inability at the given task (global failure)? Designing assessments so that setbacks are unstable (offer multiple attempts and a way for students to observe their own improvement over time) and communicating specific skills to improve (make sure feedback pinpoints how a student could improve) would help students bounce back from a “game over” scenario. But what about internal vs. external failure? For Juul, “this marks another return of the paradox of failure: it is only through feeling responsible for failure (which we dislike) that we can feel responsible for escaping failure (which we like)” (p. 54). This importance of internal failure aligns with what we know about metacognition (Berthoff, “Dialectical notebooks and the audit of meaning”) and the numerous benefits of reflection in learning.

Succeeding from Failure

Now that we have an idea on how we deal with failure, let’s consider how we can turn that failure into success! “Games then promise players the possibility of success through three different kinds of fairness or three different paths: skill, chance, and labor” (Juul, p. 74):

Skill: Learning through failure, emphasis on improvement with each attempt. (This is also very motivating by being competence-supportive!)
Chance: We try again to see if we get lucky.
Labor: Incremental progress on small tasks accumulates more abilities and items that persist through time and multiple play sessions. Emphasis here is on incremental growth over time through repetition. (Animal Crossing is a great example.) (This path is also supported by Dweck’s growth mindset.)

Many games reward players for all three of these paths to success. In an online course, allowing flexibility in assignment strategies can help students explore different routes to success. For example, a final project could allow for numerous format types, like a paper, podcast, video tutorial, interactive poster, etc. that students choose strategically based on their own skills and interests. Recognizing improvement will help students with their skills and helping students establish a routine of smaller, simpler tasks that build over an entire course can help them succeed through labor. Chance is an interesting thing to think about in terms of courses, but I like to think of this as it relates to content. Maybe a student “gets lucky” by having a discussion topic align with their final project topic, for example. For the student in that example, that discussion would come easier to them by chance. Diversifying content and assignment types can help different individuals and groups of students feel like they have “lucky” moments in a course.

Reflecting on Failure

Finally, how do games give us the opportunity to reflect on our successes and failures during gameplay? Juul outlines three types of goals that “make failure personal in a different way and integrates a game into our life in its own way” (pp. 86–87):

Completable Goal: Often the result of a linear path and has a definite end.
1. These can be game- or player-created. (i.e., Game-Driven: Defeat the ghost haunting the castle. Player-Driven: I want to defeat the ghost without using magic.)
Transient Goal: Specific, one-time game sessions with no defined end, but played in rounds. (e.g., winning or losing a single round of Mario Kart.)
Improvement Goal: Completing a personal best score, where a new high score sets a new goal.

For Juul, each of these goal-types have different “existential implications: while working toward a completable goal, we are permanently inscribed with a deficiency, and reaching the goal removes that deficiency, perhaps also removing the desire to play again. On the other hand, we can never make up for failure against a transient goal (since a lost match will always be lost), whereas an improvement goal is a continued process of personal progress” (pp. 86–87). When thinking about your courses, what kinds of goals do you design for? Many courses have single-attempt assignments (transient goal), but what if those were designed to be improvement goals, where students worked toward improving on their previous work in a more iterative way that replaced old scores with new and improved scores (improvement goal)? Are there opportunities for students to create their own challenging completable goals?

I hope this post shines a light on some different ways of thinking about assessment design, feedback types, and making opportunities for students to “fail safely” based on how these designs are achieved in gaming. To sum everything up, “skill, labor, and chance make us feel deficient in different ways when we fail. Transient, improvement, and completable goals distribute our flaws, our failures, and successes in different ways across our lifetimes” (Juul, p. 90).

Introduction to Intersectionality

In 1989, Kimberlé Williams Crenshaw, a lawyer and scholar of Critical Race Theory (CRT), coined the term intersectionality to describe the multiple and layered oppressions experienced by African American women. Over time, this term has been used to describe many aspects of social identity, particularly focusing on race, gender, and class oppression. Intersectionality allows us to consider the impact of multiple oppressions on individuals and groups. For example, asking what it means to be poor in the United States is different from asking what it means to be a poor, Black, woman in the United States, which is different from asking what it means to be a poor, Black, disabled woman in the Southern United States.

Intersectionality matters because, if we don’t recognize and support our most marginalized citizens, they will continue to fall through the cracks. In colleges and universities, this means that our most marginalized students may need additional support to perform to their full potential. Addressing one source of oppression may not provide enough support to students who are working to overcome multiple sources of oppression.

Disability in Higher Ed

Disability is an obstacle for many college students. Consider these statistics:

19% of undergraduate students report having a disability.
28% of American Indian/Alaska Native students reported a disability.
21% of White students reported having a disability (rounded to nearest percent).
17% of the students with disabilities are Black. (National Center for Educational Statistics [NCES], 2019).

When considering disability–or any other identity–we need to consider how other characteristics might compound the marginalization of students with disabilities. Let’s consider how race intersects with disability.

While the percentage of Black people with disabilities in higher education is lower than the percentage of White people with disabilities in higher education, in the general population, the reverse is true. According to Courtney-Long, E.A., Romano, S.D., Carroll, D.D. et al. (2017), 1 in 4 Black people have a disability, while 1 in 5 White people have a disability. This means that more white people with disabilities are accessing and progressing through higher education.

It is also important to recognize that the actual percentages of students with disabilities is higher as many students choose not to disclose their disabilities to their institutions. According to one study, “9% of students who identified as disabled did not disclose this information to their college or university” (Taylor & Shallish, 2019, p. 10).

There are clearly opportunity and equity issues that disproportionately impact students of color with disabilities in higher education.

Yet, when we work to create learning environments that are inclusive of students with disabilities, we often neglect to address intersecting sources of oppression. For example, accessibility requirements do not consider how disability intersects with other oppressions, such as class or race.

Universal Design for Learning

Universal Design for Learning (UDL) is an approach that is commonly cited as a way to meet the needs of all learners. UDL includes a framework with three general principles (multiple means of engagement, multiple means of representation, and multiple means of action and expression) each of which includes multiple guidelines and checkpoints for actual practice (CAST.org, n.d.). The goal of UDL is to increase access and usability for the greatest number of people possible. A UDL approach is structured and practical and, despite the critiques included here, is lauded for its utility by course designers and teachers alike.

UDL, however, does not meet the needs of all learners, particularly our most marginalized learners. Let me repeat: UDL does not meet the needs of our most marginalized learners, as much as we would like to believe it does. Let me highlight a few of the reasons for this.

As Dolmage (2017) explains in the book Academic Ableism: Disability and Higher Education, UDL’s emphasis on universality is problematic because universality is connected to normativity. (p. 134). Dolmage (2017) states that UDL has gained recognition by appealing to the majority, but in doing so “the needs of the majority once again trump the needs of those who have been traditionally excluded—people with disabilities” (p. 135). UDL is viewed as a framework for addressing the needs of disabled students, but its actual emphasis is on meeting the needs of the majority.
With its emphasis on “multiple means” UDL aims to include multiple learner identities and preferences; however, it “overlooks the importance of feedback from its own users” (Dolmage, 2017, p. 126). In this way, UDL ignores the individual circumstances of actual students.
By focusing on the “means,” over the students themselves, UDL is not an intersectional approach to design and teaching. Defining what a Universal Design looks like without considering the particularized realities of actual students results in the continued marginalization and erasure of students who are not in the majority.

UDL has popularized educational practices that serve many students, but in doing so, it has effectively erased the needs of some of the most marginalized students–those with disabilities. Those students with disabilities who are also part of other oppressed groups are increasingly at a disadvantage.

There’s no doubt that UDL is an incredibly useful tool and makes our course designs better, but we must not fail to recognize that UDL is not a panacea. UDL should be one of many tools we use to meet the needs of students, but let’s not forget that we need a truly intersectional approach to design and teaching. Without this, we, unwittingly or not, are contributing to the marginalization and erasure of our most disadvantaged students.

References

About Universal Design for Learning. (n.d.). CAST.org. Retrieved on June 8, 2020 from http://www.cast.org/our-work/about-udl.html

Courtney-Long, E.A., Romano, S.D., Carroll, D.D. et al. (2017). Socioeconomic Factors at the Intersection of Race and Ethnicity Influencing Health Risks for People with Disabilities. J. Racial and Ethnic Health Disparities, 4, 213–222. https://doi.org/10.1007/s40615-016-0220-5

Dolmage, J. (2017). Universal Design. In Academic Ableism: Disability and Higher Education (pp. 115-152). Ann Arbor: University of Michigan Press. Retrieved June 8, 2020, from www.jstor.org/stable/j.ctvr33d50.7

Taylor, A. & Shallish, L. (2019). The logic of bio-meritocracy in the promotion of higher education equity, Disability & Society, DOI: 10.1080/09687599.2019.1613962

U.S. Department of Education, National Center for Education Statistics. (2019). Digest of Education Statistics, 2017 (2018-070), Chapter 3. Retrieved June 10, 2020 from https://nces.ed.gov/fastfacts/display.asp?id=60

“Man Reading Touchscreen” | Image by Karolina Grabowska from Pixabay

Background

Five years ago, I wrote a small entry in the ORTESOL Newsletter about the then state of “adaptive software capable of teaching, testing, giving feedback, and most importantly, adjusting to student needs” (Chambers, 2015: 13). I mentioned a set of technologies colloquially referred to as the “Digital Aristotle”, or ‘Project Halo’ (Friedland et al., 2004), and the update to this six years later (Gunning et al., 2010). The Digital Aristotle was described as ‘an application that will encompass much of the world’s scientific knowledge and be capable of applying sophisticated problem-solving to answer novel questions’ (Friedland et al., 2004).

At the time, I was writing about a more grandiose piece of software that might one day replace the repetitive tasks of an ESOL classroom. The idea, or perhaps the concern about this technology for existing teachers was where they would fit in once a set of algorithms could replicate much of the day to day learning of a language course.

Five years on, I turn to how learning designers might be able to incorporate AI into course design.

Potential

First, a question: is there currently a program capable of teaching a course and adapting to student needs like an instructor? The answer is still no. Certain technology has, however, progressed to the point that portions of an online course can be enhanced by AI.

Adaptive Learning

Quite possibly the most exciting development in artificial intelligence for learning is that of adaptive learning. This concept has been in the works for a while with certain platforms utilizing algorithms to produce content that adapt to specific learner needs.

Instructure’s Canvas for instance, allows Instructional Designers to set up ‘Differentiated Assignments’ (Canvas Doc Team, How do I view differentiated assignments with different due dates in a course?, 2017) and ‘MasteryPaths’ (Canvas Doc Team, How do I use MasteryPaths in course modules?, 2020) which ‘allows targeted learning activities to be assigned to different users and sections’ (‘MasteryPaths’). Currently this is a manual process with course designers creating every assessment beforehand. The best students might not see the additional activities. It is not ‘intelligent’ in the way that course content is adapted specifically for a learner’s needs and on the fly. To do this requires large amounts of data and most importantly, AI training to see patterns, strengths, and weaknesses for a particular learner.

This is why Duolingo records progress at every step and offers learners a review of concepts the learner struggles with in previous activities. Platforms that provide an automated review often use large question banks and flag questions that learners initially, or continuously incorrectly answer. An intelligent AI could create novel questions based on learner goals, data from prior students, and information about the subject matter. An example of this is Google or Amazon’s ability to predict and offer products or suggestions based on the vast amount of information provided to them every single day. Certain training providers are currently working with application developers to produce tools capable of this on-the-fly feedback and adaptation.

Discussions

At the OLC Innovate 2020 conference, Kasey Gandham from Ed Tech company Paperback and Kim A. Scalzo, Executive Director of Open SUN, demonstrated how Paperback’s AI is being used with online discussions to help students write higher quality posts. As students write their discussion posts, the AI program checks for “close-ended questions, plagiarism, insufficient length, content about class logistics, profanity and abuse’ (Gandham & Scalzo, 2020). After this, if required, the post is moderated and the learner receives email feedback saying why and how to revise their post. The AI is also capable of suggesting posts to feature as the best of the week by analyzing, among other things, sentence depth and ‘curiosity score’.

More than a Quiz

The role and importance of ‘big data’ in online learning cannot be understated. Technology already exists that records the time learners interact with learning materials. It knows where they are clicking/tapping on the screen and how long activities hold learner attention. Using this data, AI could suggest, or even craft assessments that are adapted specifically to a single learner’s usage habits. Traditional quizzes which assess information retention could become only part of the larger formative assessment of the entire course, at every point in the course, without the learner even realizing any of this is happening.

Future

AI-enhanced design has the ability to transform Instructional Designers like never before. It could help us to modify our own design practices based on how learners are responding to course content. Through learner feedback, it could demonstrate which activities are most appealing and conducive to personalized learning goals. Big data’s role in recording learner interactions with content can provide insights into preferred learning styles and methods of instruction. Instructional Designers will have to continue adapting with the technology just as we have done in our everyday lives.

References

Canvas Doc Team. (2017, April 19). How do I view differentiated assignments with different due dates in a course? Retrieved July 02, 2020, from https://community.canvaslms.com/docs/DOC-10036-how-do-i-view-differentiated-assignments-with-different-due-dates-in-a-course

Canvas Doc Team. (2020, April 6). How do I use MasteryPaths in course modules? Retrieved July 02, 2020, from https://community.canvaslms.com/docs/DOC-26231-how-do-i-use-masterypaths-in-course-modules

Chambers, P. (2015, Spring). “Digital Aristotle” and ESL: What does it mean for us?. ORTESOL Quarterly Newsletter, 38(1), P.12-13.

Friedland, N.S. et al. (2004). ‘Project Halo: Towards a Digital Aristotle’, American Association for Artificial Intelligence, 25(4), pp. 29-47. DOI: http:// dx.doi.org/10.1609/aimag.v25i4.1783.

Gandham, K. and Scalzo, K., A. (2020, June). USING AI IN DISCUSSION TO SCALE ACCESS TO QUALITY ONLINE EDUCATION. OLC Innovate 2020, Online Presentation. https://onlinelearningconsortium.org/olc-innovate-2020-session-page/?session=8486

Gunning, D. et al. (2010). ‘Project Halo Update – Progress Toward Digital Aristotle’, Association for the Advancement of Artificial Intelligence, 31(3), pp. 33-58. DOI: http:// dx.doi.org/10.1609/aimag.v31i3.2302.

New online instructors often express concern about the loss of immediate student feedback they get by teaching in person. These educators count on in-class interaction to help shape their lesson plans in real-time. Student questions, lack of interaction, or even blank looks, help them understand what concepts are difficult for their learners. Others just feel more comfortable with the two-way nature of in-classroom communication.

But teaching in an online environment doesn’t have to be mutually exclusive from gauging student interest and comprehension.

Mud Cards

I was first introduced to the concept of “Mud Cards” or “Muddiest Points” through an open course MIT offered in Active Learning in College-Level Science and Engineering Courses. The instructor described handing out index cards to each student at the end of class asking students to write down an answer to one or more of a few prompts (MIT OpenCourseWare, 2015).

In an online course, this could easily take the form of a weekly survey that looked something like this:

What concept from this week did you find confusing?
Is there anything you found particularly compelling?
What would you like to know more about?

Potential Benefits

The answers received have multiple potential benefits. First of all, instructors will get to look for trends in a particular class.

Are learners missing something central to a course learning outcome?
Is there a concept they need additional resources to master prior to an upcoming exam?
What excites them the most?

Getting this information weekly can provide information that is normally gathered during in-class interactions. It may even be more informative, as participation is likely to be higher (or can be incentivized through participation points). This feedback can be used to add content, perhaps through an announcement at the beginning of the next unit, addressing any common problems students reported. It can also help improve the content or activities for the next iteration of the online course.

The second benefit of an activity like this one is that it is an easy way to introduce active learning to your online course. Active learning, with origins in Constructivism, includes the idea that students build knowledge through “doing things and thinking about what they are doing.”

Rather than passively watching narrated slide-based lectures or videos, or completing assigned readings, they are asked to think about what is being taught to them. Each student, by reflecting on questions like the examples above, takes some responsibility for their own mastery of the content.

3-2-1 (a similar tool)

I recently attended the keynote at the Oregon state Ecampus Virtual Faculty Forum by Tracey Tokuhama-Espinosa (Tokuhama-Espinosa, 2020). At the beginning of her presentation, she told all of us we were going to be asked to email her our “3-2-1.” A 3-2-1, she defined as:

Three things that are new to me
Two things so interesting I will continue to research or share with someone else
One thing I will change about my practices based on the information shared today

Even though I was very familiar with the underlying pedagogical practice she was leveraging, I paid significantly more attention than I would have otherwise to an online presentation. I wanted to come up with something helpful to say. To be honest, suffering from COVID related ZOOM fatigue, it also made sense to ensure the hour of my time resulted in something actionable.

A Word of Caution

The use of a tool like the Mud Cards or 3-2-1 will be successful only if used consistently and students see the results of their efforts. If not introduced early and repeated regularly, students won’t develop the habit of consuming content through the lens of reflecting on their own learning. Similarly, students who never see a response to their input, through a summary or additional explanations, will get the message that their feedback is not important and lose the incentive to continue to provide it.

Conclusion

Introducing a reflection activity like those suggested is a simple, quick way to incorporate active learning into a course while simultaneously filling a void instructors sometimes miss through being able to ask questions of their students in a classroom.

Canvas allows for building anonymous graded or ungraded surveys in which a weekly activity like this would be easy to link to in a list of tasks for a unit of study. It is a low development effort on the part of the instructor, and participation from students shouldn’t take more than 5 minutes.

I will link below to some of the resources mentioned that discuss the use and benefits of Mud Cards and active learning in instruction. If you try it out in an online course, I would love to hear how it works for you.

Resources

How Do I Create a Survey in My Course? Canvas LMS Community, 6 Apr. 2020
Hall, S. R., et al. “Adoption of Active Learning in a Lecture-Based Engineering Class.” 32nd Annual Frontiers in Education, vol. 1, IEEE, 2002, pp. T2A-9-T2A-15. DOI.org (Crossref), doi:10.1109/FIE.2002.1157921.
Rankin, Janet. Teaching College-Level Science and Engineering. 2015. ocw.mit.edu.
Tokuhama-Espinosa, T. (2020, May 5). Faculty Forum 2020—Keynote—Never a Better Time to Be an Educator! Ecampus Faculty Forum Special Virtual Event, Oregon State University Ecampus

Rainboots photo by Daiga Ellaby on Unsplash

Lately I’ve heard from a number of faculty whose students have expressed stress or overwhelm at the workload in a course. Further, students as well as faculty have had to adjust to a new routine or pace in their lives in recent months. All of this change gives us a chance to examine the workload and pace of a course so that it is manageable for both students and instructors. To that end, I offer three simple things that faculty can do to make their workload more manageable:

Manage expectations
Post time estimates for each activity
Consider your own availability

Manage expectations

One of the most effective ways to help students understand how much they should plan to do each week in the course is to be explicit and specific about the workload, early in the course. Refer to the credit hour policy to help students understand expectations. At OSU, it is expected that students engage with course materials and activities for 3 hours per week for every credit hour. So for a 3-credit course, students should expect to work about 9 hours each week on reading, studying, assignments, discussion boards, and other activities. This information is generally listed in the syllabus, but it’s nice to highlight this in an announcement early in the course, or perhaps even in an intro video or weekly overview video. Being explicit early in the course sets expectations for everyone, builds trust, and cuts down on negative emotions from students who feel there is too much (or not enough) in a course.

Post time estimates for each activity

One complaint that students occasionally have is that there is an uneven workload from week to week. One way to address this is to post estimated times for each activity for the week. This could appear in a task list on a weekly overview page, for example. This helps in several ways. First, it helps students who struggle to manage their time effectively. If they know that the assignment takes about 2 hours to complete, they can plan for that chunk of time in their week. Moreover, perhaps there are six readings posted in one week, but each reading is only about 5-10 minutes long. Posting this helps students understand that there are a number of short readings this week. That way students don’t assume each reading takes too long and decide to skip some of them. Moreover, being explicit about time estimates helps students know that you are sticking with the credit hour policy as well, which is another way to build trust.
If you find that the tasks you’ve outlined exceed the credit hour policy, let your learning objectives for the course guide your decisions for what to keep and what to cut.

Consider your own availability

Lastly, consider your own availability. Be explicit with students about when you are available so that you can be sure to carve out time to recharge your batteries. For example, if you like to have a bit of time to relax on the weekends, you might have your weekly assignments due on Monday of the following week for each module, rather than Sunday. That way, if students have questions about an assignment that they are wrapping up over the weekend, you still have Monday morning to get back to them instead of scrambling to answer multiple emails on Sunday evening.

In part one of Academic Success, we reviewed why it is important to help students develop time management skills and how to design courses that help students manage time. In this post, we will discuss the why, what and how about teaching students how to learn.

By this time, most public schools and higher education institutions are coming to a close for Spring 2020 teaching. Congratulations on overcoming so many challenges and finishing teaching during COVID-19! As we prepare for summer and/or fall teaching, I would like to invite instructors to consider teaching students how to learn in your next teaching adventure, in order to help students achieve academic success.

Why Teach Students How to Learn?

For teachers, teaching students how to learn enables them to facilitate dramatic improvements in student learning and success (McGuire & McGuire, 2015).

For students, metacognition helps them to become self-aware problem solvers and take control of their own learning, through taking stock of what they already know, what they need to work on, and how best to approach learning new material (The Learning Center at UNC Chapel Hill, n.d.).

Teaching students how to learn also aligns tightly with the neuroscience of how humans learn. Dr. Daniela Kaufer pointed out four key learning principles based on the neuroscience of how people learn: (1). Learning involves changing the brain; (2). Moderate stress is beneficial for learning, while mild and extreme stress are detrimental to learning; (3). Adequate sleep, nutrition, and exercise encourage robust learning; and (4). Active learning takes advantage of processes that stimulate multiple connections in the brain and promote memory (Kaufer, 2011).

What to Include in “Teach Students How to Learn”?

Now we have seen why it is important to teach students how to learn from the perspectives of teachers, students and neuroscience, it is time to look into the content of a “Teaching Students How to Learn” training module. Dr. Saundra McGuire suggests getting students’ buy-in as a first step, through early diagnostic assessment which can be used to find out what students already know and what they did not know. Past examples of dramatic increase in assessment performance after receiving “Teaching Students How to Learn” training can also be an effective way to gain students’ buy-in. Secondly, Dr. McGuire suggests teaching students Bloom’s Taxonomy and study cycle to help students self-evaluate what they are learning and where to focus their learning at (the higher levels of learning, such as the applying, analyzing, evaluating and creating). The Study Cycle includes preview, attend, review, study and assess (Cook, Kennedy & McGuire, 2013). Thirdly, Dr. McGuire suggests sharing metacognitive learning strategies with students. The Learning Center at University of North Carolina at Chapel Hill lists eleven specific strategies that students can use to enhance their learning: (1) use your syllabus as a roadmap; (2) summon your prior knowledge; (3) think aloud; (4) ask yourself questions; (5) use writing; (6) organize your thoughts using concept maps or graphic organizers; (7) take notes from memory; (8) review your exams using test analyzer tool; (9) pause and ask yourself why you are doing what you are doing and how what you’re doing relates to the course as a whole and to the learning objectives that your professor has set; (10) test yourself; and (11) figure out how you learn and what learning strategies work best for you.

How: Implementing “Teach Students How to Learn” in Online Course Design

There are many ways teachers and instructional designers can build activities and structures in course design to teach students how to learn. The following list is a starting point:

Provide specific, measurable, attainable, result-focused and time-focused objectives at both course level and module level, and ask students how these objectives connect to their own learning interests and objectives, for example, using an ungraded survey/poll/private check in at the start of the term.
Provide opportunities for students to reflect on prior knowledge they bring to the target topic/course
Provide a list of questions to guide students for targeted reading and better reading comprehension as an active reading strategy, when assigning required readings materials.
Provide questions in video lectures to help students check their understanding and keep students engaged;
Release answer sheet to homework assignments after submission expires and provide opportunity for students to compare what they did right or wrong and how to get it right if they did it wrong initially, to achieve mastery learning;
Provide opportunities for peer review and instructor feedback and make it possible for students to resubmit edited versions based on feedback received for mastery learning;
Allow multiple attempts for assignments and assessments for mastery learning;
Provide opportunities for students to reflect around midterm what learning strategies they use, whether they are effective or not, and how to adjust for better results in the reminding time of the course.
Provide opportunities for students to reflect near the end of the term on what they learned and how they have learned, and how they might use the learning in their lives. For example, using discussion forum, google form survey, quiz or assignment to collect students’ reflective feedback.

The list can go endless. The point is there are many opportunities for teachers and instructional designers to build elements in course design to teach students how to learn! Feel free to share your ideas or experience of teaching students how to learn with us.

References

Cook, E., Kennedy, E., and McGuire, S.Y. (2013). Effect of Teaching metacognitive learning strategies on performance in General Chemistry Courses. Journal of Chemical Education, 2013, 90, 961-967.

Kaufer, D. (2011). Neuroscience and how students learn. University of California Berkeley Graduate Student Instructor Teaching & Resource Center. Retrieved from https://gsi.berkeley.edu/gsi-guide-contents/learning-theory-research/neuroscience/

McGuire, S. Y., and McGuire, S. (2015). Teach Students How to Learn : Strategies You Can Incorporate into Any Course to Improve Student Metacognition, Study Skills, and Motivation. First ed. Sterling, Virginia: Stylus, LLC.

The Learning Center, University of North Carolina at Chapel Hill. (n.d.). Metacognitive Study Strategies. Retrieved from https://learningcenter.unc.edu/tips-and-tools/metacognitive-study-strategies/

Resources on Neuroeducation

Adolphs, R. (2009). The social brain: neural basis of social knowledge. Annual Review Psychology. 2009; 60: 693-716.
Bransford, John., and National Research Council . Committee on Developments in the Science of Learning. How People Learn : Brain, Mind, Experience, and School. Expanded ed. Washington, D.C.: National Academy, 2000. Print.
CAST (2018). UDL and the learning brain. Wakefield, MA: Author. Retrieved from http://www.cast.org/our-work/publications/2018/udl-learning-brain-neuroscience.html
Doyle, Terry, and Zakrajsek, Todd. The New Science of Learning How to Learn in Harmony with Your Brain. Second ed. Sterling, Virginia: Stylus, LLC, 2019. Web.
Eyler, J. (2018). How humans learn : The science and stories behind effective college teaching(First ed.), Teaching and learning in higher education (West Virginia University Press)). Morgantown: West Virginia University Press.
Kaufer, D. (2011). Neuroscience and How Students Learn. Berkeley Graduate Student Instructor Center’s How Students Learn Series talk in Spring 2011. Retrieved from https://gsi.berkeley.edu/gsi-guide-contents/learning-theory-research/neuroscience/
McLagan, Pat. “Unleashing the Unstoppable Learner.” Talent Development7 (2017): 44-49. Web. https://www.td.org/newsletters/atd-links/being-a-lifelong-learner
Perkins, D. N., Goodrich, H. , Tishman, S. & Owen, J. M.(1994). Thinking Connections : Learning to Think and Thinking to Learn. Menlo Park, Calif.: Addison Wesley, 1994. Print.
Schwartz, Daniel L., Tsang, Jessica M., and Blair, Kristen P. The ABCs of How We Learn : 26 Scientifically Proven Approaches, How They Work, and When to Use Them. First ed. New York, NY: W.W. Norton &, 2016. Print. Norton Books in Education.
Südhof, T.C. (2013). Neurotransmitter release: the last millisecond in the life of a synaptic vesicle. Neuron. 2013 Oct 30;80(3):675-90. doi: 10.1016/j.neuron.2013.10.022.
Tokuhama-Espinosa, Tracey (2011). Mind, Brain, and Education Science: A Comprehensive Guide to the New Brain-Based Teaching.New York: W. W. Norton.
Ware, D. (2013). Neurons that fire together wire together. Retrieved from https://www.dailyshoring.com/neurons-that-fire-together-wire-together/

A student persona is a summary of a specific type of student. This persona represents archetypes NOT stereotypes of a broader student segment or group. A student persona summarizes who the student users are and why they are using the learning system, as well as what behaviors, assumptions, and expectations determine their view of the learning system.

Why Create Student Personas?

There are many reasons why instructors and instructional designers and developers create and use student personas, such as:

To represent the major needs of the key student user groups.
To provide a reliable and accurate representation of your targeted student audience.
To enable you to focus on a manageable and memorable group of students.
To help you create different designs for different kinds of students and to tailor the design to meet the needs of the most important student user groups.
To inform on the functionality of the learning system, uncover gaps in instructional design and development, or highlight new ways to deliver learning.

What Makes Up a Student Persona?

Like all personas, student personas generally include several key pieces of information, which are outlined on usability.gov

Here is an example of a student persona that I created for an online Intro to Permaculture MOOC that includes the essential elements of a persona.

Student Persona Example Description of the user research conducted to create the student persona:

Student user research was conducted through an online Welcome survey that was embedded in the online course. As in all persona creations, user research should be conducted and the collected data should be used in order to ensure accurate representations of your users. Student user research can be conducted online or face-to-face through student surveys, interviews, or observations.

Student Persona Example (Enlarged View)

How Are Student Personas Used?

More than one student persona (3-5 student personas) should be used for an instructional development project from the analysis phase to the design, development, implementation and evaluation. As such, these student personas can be used in numerous ways.

Smashing Magazine, A Closer Look at Personas – What They Are and How They Work, discusses some of the general uses of personas:

Build empathy
Develop focus
Communicate and form consensus
Make and defend decisions
Measure effectiveness

Resources

While there is no one way to create and use a persona, there are plenty of examples, free templates, and instructional videos and readings available to help you get started to create personas of the students that you serve and to use them in your instructional developments. These resources are available through the following links.

Examples

Tobi Day
Rita

Templates

Fake Crow Free Persona Template
Persona Core Poster Template | PDF

Video

How to Create UX Personas (3:01)
(Note: This video talks about service design for customers, but for student personas, you will want to keep in mind that the students and learners are the customers)

Readings

Personas by usability.gov
A Closer Look at Personas – What They Are and How They Work by Smashing Magazine

This is a re-publish of a prior blog post that is quite popular and we wanted to bring it to the top of the blog again. Thank you to our original author: Rebecca Pietrowski

Transparency

Purpose

Task

Grading Criteria

Remarks

Sources

Dealing with Failure

Succeeding from Failure

Reflecting on Failure

Introduction to Intersectionality

Disability in Higher Ed

Universal Design for Learning

References

Background

Potential

Adaptive Learning

Discussions

More than a Quiz

Future

References

Mud Cards

Potential Benefits

3-2-1 (a similar tool)

A Word of Caution

Conclusion

Resources

Manage expectations

Post time estimates for each activity

Consider your own availability

Why Teach Students How to Learn?

What to Include in “Teach Students How to Learn”?

How: Implementing “Teach Students How to Learn” in Online Course Design

References

Resources on Neuroeducation

Why Create Student Personas?

What Makes Up a Student Persona?

How Are Student Personas Used?

Resources

Examples

Templates

Video

Readings

Contact Info