These questions are intended to guide a discussion regarding your online learning program and course design as well as online teaching and learning practices. They can be considered by individuals but are best explored as a program teaching group to consider the students’ learning across a program. Where possible, we have embedded links within the questions to further resources you may wish to explore.
The questions are organized using the Community of Inquiry (COI) framework, which summarizes the relationships in the teaching and learning space and outlines ways in which these can be replicated and enhanced in the online environment (Garrison, Anderson & Archer, 2000). In this framework, teaching and learning relationships are conceptualized as ‘presences.’ Social presence is the sense of community and safety developed in the learning environment that allows students to engage with their learning and with others (Garrison, 2009). Teaching presence points to the activities guided by the teacher, including design, facilitation and directing the social and cognitive processes of the students, all of which lead to meaningful learning outcomes. Finally, cognitive presence refers to the process by which learners construct and sustain new learning through engagement and reflection (Anderson, Rourke, Garrison, & Archer, 2001).
The three presences dynamically interact to create the learning experience of our students:
Given the emphasis on context in the Community of Inquiry framework, there is no prescription for developing a high-quality online learning experience. Developing an online course requires reflection on the teaching and learning techniques with which you may already be familiar, engagement with teaching and learning with which you may not be familiar, and additional flexibility and digital fluency skills required by the use of new technologies. The delivery of an online learning experience must be designed with reference to the students taking the course, the amount of experience they have with different types of learning environments and their access to technology (Cleveland-Innes & Wilton, 2018).
(Click on the hyperlinks to be guided to further information and explanation.)
Curriculum design decisions are influenced by the teacher’s, program’s, institution’s and discipline/field’s pedagogies. When we focus on the pedagogy (instead of solely the technology), the design and delivery should provide quality outcomes and high student engagement and satisfaction (Sharples, 2019). Some key pedagogies/philosophies to consider are:
Often referred to as the learning theory for the digital age, connectivism posits knowledge in the connection between 'nodes' of a network. Knowledge exists beyond the space of any single individual and is not controlled or created in any formal way. As a learning theory, connectivism shifts our underlying understanding of what knowledge is and how it is created – or not (knowledge as construct vs. knowledge as thing). A connectivist theory allows for the everchanging and evolving nature of knowledge in the digital age to be captured. It brings forward the spaces of creation, shared understanding, and emergence and de-emphasizes the notions of transferring knowledge. “[Connectivism] emphasizes the learner’s ability to navigate information: the pipe is more important than the content within the pipe.” (Siemens, 2005)
Connectivism would argue that previous learning theories are outdated as they have not taken into account the new environment of the information age. All previous learning theories seated knowledge within individuals and sought to explain its transfer between them. Even as knowledge grew and shifted, it was always housed within the individual. Connectivism seats knowledge outside the individual – beyond the individual. This is what makes connectivism the learning theory for the digital age – it has allowed knowledge to transcend its linear transference and exist in the space around us, in our connections, and in our connected spaces.
Siemens (2005) identifies the principles of connectivism as follows:
The intersections between Indigeneity and digitalization are complex. Digitalization has the potential to expand Indigenous representation and connect Indigenous communities in solidarity and strategic alliance (Beltrán & Begun, 2014). Indigenous knowledge systems, including innovations, can become more readily available to learners (teachers and students) through technology. However, they must be understood within the context of the communities from which they originate (Archibald/Xiiem, 2018; Hopkins, 2006).
Digital pedagogies situated within Indigenous methodologies can help Indigenous youth to develop sensibilities (voice) and technical skills to engage in the digital economy and digital citizenship. However, machine technologies and infrastructures are largely colonial in design and ownership (Hearne, 2017). Aspects of digital media, including its modularity, fragmentation and dispersion also structure racism and racial representation (Byrd, 2014; Hearne, 2017). Despite this, there is a long history of Indigenous digital engagement that has subverted the colonizer's indoctrination (Hopkins, 2006) in order to preserve and evolve cultural knowledge, counter colonial narratives and connect diverse lndigenous communities in solidarity (Lucas, 1996; Michel, 2019).
Open pedagogy adoption is not just about Open Educational Resource (OER) adoption; embracing OERs requires the institution to commit to fostering an open culture (i.e. give staff time to develop OER resources, providing training on how to embrace this as a practical teaching and learning strategy, and thinking differently about how we involve learners in content creation, curation, and assessment). Open pedagogy asks us to consider the creative commons space and our justifications for an open approach within a larger context. Undoubtedly, scholars cite the benefits OER adoption as increasing student learning while breaking down barriers of affordability and accessibility. In a 2012 study, Feldstein et al. conducted a research study at Virginia State University, where OER were implemented across nine different courses in the business department. Researchers found that students in courses that used OER more frequently had better grades and lower failure and withdrawal rates than their counterparts in courses that did not use OER. However, there are other contextual variables that might be affected and should be considered. What are the access limitations of moving material to a digital space? Is it wrong to assume that students are only concerned about their financial bottom line when it comes to their education? What is the trade-off of cheaper resources? What is the quality impact of a move to OERs? Without these considerations, it’s likely a decision to move to OERs could significantly impact the student experience and translate to zero return on investment (ROI) for students (DeRosa and Robinson, 2017).
This pedagogical approach explores the degree to which Critical Pedagogy operates in the digital teaching and learning space. It considers the way in which reflection, community, agency, and democratization can be supported in a digital space and how this support can ensure representation and access across age, race, culture, gender, ability, and geography. Teaching and learning that is guided by Critical Digital Pedagogy necessitates an emphasis on positioning learners as digital citizens and making sure they have all the technological and metacognitive abilities for full participation in this role.
Stommel (2017) outlines that Critical Digital Pedagogy:
Engaging with technology requires an investment of time to learn the technology, sometimes money and always a consideration of the technology tool’s impact on the user’s data security and privacy. All of these need to be considered when we ask learners to engage with a particular technology for their coursework (Kim, 2018).
These include both the access expected to use a certain technology (bandwidth, storage capacity etc.) as well as the digital skills students will need to use the technology effectively (JISC, 2009). Assessing students’ readiness to use technology is key as a baseline check. Of course, individuals’ skills will vary within a course and across a program. This is where a UDL perspective might help by offering different technology options and connections to training resources for these technologies. Once a baseline has been established, students can build on their digital fluency through intentional teaching and learning practices (JISC, 2009).
Keys to success in using technology in education depend primarily on how technology is used and with what intentions rather than if it is used. From a Universal Design for Learning perspective, technology can help teachers to design learning for barrier mitigation. However, technology can also present barriers to learning. Learning goals come first; technology use in the classroom is in service of these. Technology and UDL are complementary but not codependent. UDL principles can be used to inform technology choices (Black & Moore, 2019).
UDL suggests designing for learner variability (Stanford University, n.d.); in a technology-enhanced learning space, this means considering how best to utilize technology for multiple means of engagement, accessible representation and action/expression. This may result in a high-tech offering, but could just as easily be low-tech (Lombardi, 2019).
Here are a few ways you can use UDL in an online space to increase access, engagement and learning outcomes for students.
There is no magic ratio for what portion of the course or program is synchronous compared to asynchronous. It will depend on your learners’ needs and your own technological access and skills. The followed table, adapted from Cleveland-Innes & Wilton (2018), may help you decide on the right mix for your program or course.
|Synchronous Learning||Asynchronous Learning|
• Discussion and collaboration in real time
• Immediate feedback
• Time and cost savings
• Instructor assessment of learning via observation
• Increased engagement and motivation via social presence
• Anytime, anywhere learning
• Convenient access to course process and materials
• Time for research and reflection before responding
• Instructor assessment of learning via reflection and thoughtful response
• Written expression more thorough and detailed
• Requirement to participate in the same place at the same time
• Can require advanced technical infrastructure and skill
• Quality of engagement depends on facilitator skill
• Learner self-pacing less available
• Potential for feelings of isolation, lack of connection
• Self-pacing requires increased levels of self-direction
• Quality of engagement depends on course designer skill
• No immediate access to instructor
• Discussing less complex issues
• Getting acquainted
• Planning tasks
• Reflecting on complex issues
• When synchronous meetings cannot be scheduled because of work, family or other commitments
|Why?||• Students become more committed and motivated because a quick response is expected||• Students have more time to reflect because the sender does not expect an immediate answer|
|How?||• Use synchronous means such as videoconferencing, IM and chat||• Use asynchronous means such as email, discussion boards and blogs|
• Students expected to work in groups may be advised to IM as support for getting to know one another
• Instructor wants to present concepts from the literature in a simplified way by giving an online lecture using videoconferencing
• Student expected to reflect on a course topic and maintain blog journal
• Students may critically assess their peers’ ideas through a discussion forum
Cleveland-Innes and Wilton (2018) encourage educators to “choose your technology carefully so that all learning activities […] are well suited to the needs of the subject matter and the students.[…] Comfort and competence with the technology has to be demonstrated before the learning activities commence. Technology that supports [online] learning will support (1) flexibility and personalization for students, allowing them to learn in their own way at their own pace, and (2) activity monitoring by the teacher through learning analytics and electronic assignment submission. Consider what is to be accomplished by using learning technologies: sharing of course content, group work, peer assessment, question facilitation, fostering community [etc.] (p. 21).”
To increase development of adaptive expertise, Dumont et al. (2012) recommend a combined approach of: guided learning, active learning and experiential learning. In this model, learning becomes increasingly self-directed. Adaptive expertise harnesses emotion and motivation to enhance cognition. It also diversifies learning to include self-study AND collaboration. Including assessment FOR learning is also crucial.
Online learning, perhaps more so than face-to-face learning, requires students to be more independent. There are many ways to support students’ development of executive functioning in the online environment. At the beginning of a course and program, it’s important to develop shared expectations for how to engage in the learning environment. These ideally support the learning goals of the course or program, both the course and program outcomes and what students are hoping to achieve through their learning. The adaptive expertise model discussed above in the Expert Learning section is another way to think about scaffolding learning across and within courses. The following chart summarizes some other teaching strategies that support executive functioning in three key areas (CAST, n.d., Supports for Executive Functioning Online section):
|Planning & Organization||Design clear, interactive course headings and icons. Group content into logical learning units and divide information into small segments. Limit modules to 8–10 pages in length.|
|Goal setting, Prioritizing & Progress Monitoring||Provide checklists for making progress. Provide self-check quizzes. Give immediate feedback on quiz responses and activities.|
|Applying Learning Strategies||Provide options to create notes, annotate material, and organize materials and resources. Provide models and hints to help students get started on a problem.|
Research has proven that assessment of students, not content, shapes their understanding of the curriculum (JISC, 2007). A move to digital assessments influenced by a strong digital pedagogy can have significant benefits for students such as well-scaffolded summative assessments, more frequent formative assessments, technology-enhanced feedback of learner progress with lower effort on the part of faculty, the ability to address students’ misconceptions more quickly, more efficient plagiarism checks, and increased marking consistency and inter-rater reliability (JISC, 2010). Technology can aid the assessment process by capturing stages of skill or product development that can later be used as points of reflection. Additionally, simple digital artefacts (quiz, survey, prompt, discussion question) can provide students with formative assessment checks and instant feedback on their current understanding. These formative assessments are not only useful feedback mechanisms for learners to direct their learning journey but also enhance student motivation (JISC, 2009).
Modern learners often have high expectations of their institution’s learning environments; they depend on the convenience of using their own devices, the flexibility of a personalized learning timeline, and the agency they experience as a result of partnering on learning objectives and assessments. Assessing in the digital space should be considered across a few dimensions:
Digital considerations, where assessments are concerned, apply to design, delivery, and management but also extend to rubrics. Many students find the language used in rubrics and grade descriptors to be “subjective and vague, [however], providing more detailed criteria can paradoxically increase students’ anxieties and lead them to focus on sometimes quite trivial issues, with some students leaning heavily on rubrics and exemplars as recipes”(Rossity, 2018, para. 6). The research in this area suggests rubrics use clear language and focus only on those criteria connected to the learning outcomes they are assessing; this focus is even more important when assessing digital assignments of varying modalities due to the embedded complexities of multimodal work.
Rubrics that assess complex multimodal tasks need to reflect the efforts and skill development students engage in to complete the task. “A digital assignment isn’t a throwaway task – it often involves substantial learning, work and creativity, and its weighting within the course – in terms of time and assessment – needs to be carefully considered” (Rossity, 2018, Findings para. 4). When these assignments also require public sharing (i.e. posting to YouTube, Flipgrid, etc.) the risk to student’s privacy and identity management increase and should be considered as mechanisms for submission and review are determined. In addition, the complexity of the task increases as does the skill set required to adeptly evaluate it, resulting in a need for faculty to develop a nuanced understanding of the “complex ways in which technical skills, composition elements, modes, and meaning interact” (Curwood 2012, p. 242) in student work.
**Note: This learning module makes the overall assumption that all of the information and considerations contained in the document begin with privacy for students and faculty as a main driving force for pedagogical adoption of educational technology. It is recommended a policy and procedure document exist at institutional and program levels that identifies the rights and protections that exist for anyone using the embedded technologies and includes all instances of data collection, tracking, and usages of all collected information (active or passive).
The implementation of technology in service of learning requires careful consideration of a number of factors, many of which have been captured in existing frameworks. For example, the SECTIONS framework, updated by Bates (2014), is intended to be used by educators and educational leaders in collaboration to make decisions regarding educational technology. An alternate rubric for educators when making decisions regarding implementation of technology in their teaching is the Rubric for eLearning Tool Evaluation. "eLearning tools are defined as any digital technology, mediated through the use of a computing device, deliberately selected to support student learning. The rubric supports a multi-dimensional evaluation of functional, technical, and pedagogical aspects of eLearning Tools. " (Anstey, L.M. & Watson, G.P.L., 2018, p. 1)
In addition to these frameworks, the ADDIE model (Analyze, Design, Develop, Implement, Evaluate) offers a useful process for considering the move to the digital teaching and learning space and all the corresponding design considerations. You can review the process in more detail here and may want to consider engaging the assistance of Instructional Designers.
At the heart of using learning analytics to design and monitor your course should be the notion that “In the hands of educators, data-based visualizations of how and what a student is learning can assist instructors to develop customized instructional strategies and curricula” (Jones, 2019, p. 2) and that “education (and to an even greater extent EdTech) has misrepresented itself as objective, quantifiable, apolitical” (Stommel, 2017). The sentiments of possibility and apprehension in these quotes make it important to always consider the use of technology and learning analytics from a critical (not dismissive or pessimistic) lens. It is of paramount importance that data users understand the embedded and underlying assumptions in the analysis of this kind of data.
The intersection of learning analytics and Universal Design for Learning can provide some encouraging and thoughtful ways to incorporate the use of data into your course design. You can find excellent resources for using data to inform course design in this UDL on Campus article.
Anderson, T., Rourke, L., Archer, W., & Garrison, R. (2001). Assessing teaching presence in computer conferencing transcripts. Journal of the Asynchronous Learning Network 5(2).
Archibald, J. & Xiiem, Q. Q. , J. & Xiiem, Q. Q. (2018). Indigenous Storytelling. In Tortell, P., Turin, M. & Young, M. (Eds.) Memory. Peter Wall Institute for Advanced Studies.
Bates, T. (2014). Choosing and using media in education: The SECTIONS model. In Teaching in a Digital Age. Retrieved from https://opentextbc.ca/teachinginadigitalage/part/9-pedagogical-differences-between-media
Beltrán, R., & Begun, S. (2014). ‘It is Medicine’: Narratives of Healing from the Aotearoa Digital Storytelling as Indigenous Media Project (ADSIMP). Psychology and Developing Societies, 26(2), 155–179. https://doi.org/10.1177/0971333614549137
Black, J. & Moore, E. (2019). UDL Navigators in Higher Education: A field guide. CAST, Inc.
Byrd, J. A. (2014) Tribal 2.0: Digital Natives, Political Players, and the Power of Stories. Studies in American Indian Literatures, 26 (2), pp. 55-64.
CAST. (n.d.) Executive functioning in online environments. Retrieved from http://udloncampus.cast.org/page/teach_executive
Cleveland-Innes, M. & Wilton, D. (2018). Guide to Blended Learning. Burnaby, BC; Commonwealth of Learning.
Curwood, J.S. (2012). Cultural shifts, multimodal representations, and assessment practices: A case study. E-Learning and Digital Media, 9(2), 232-244.
DeRosa, R & Robison S. (2017). From OER to Open Pedagogy: Harnessing the Power of Open. In: Jhangiani, R S and Biswas-Diener, R. (eds.) Open: The Philosophy and Practices that are Revolutionizing Education and Science. pp. 115–124. London: Ubiquity Press.
Dumont, H., Istance, D., & Benavides, F. (Eds.). (2010). The nature of learning: Using research to Inspire practice. OECD Publications: Paris, France. Retrieved from http://www.oecd.org/education/ceri/50300814.pdf.
Feldman, A. et. al. (2012). Open Textbooks and Increased Student Access and Outcomes. European Journal of Open and Distance Learning. Retrieved from https://www.eurodl.org/?p=archives&year=2012&halfyear=2&article=533
Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2-3), 87-105.
Garrison, D. R. (2009). Communities of inquiry in online learning: Social, teaching and cognitive presence. In C. Howard et al. (Eds.), Encyclopedia of distance and online learning (2nd ed., pp. 352-355). Hershey, PA: IGI Global.
Higher Education Funding Council of Europe. (2010). Effective Assessment in a Digital Age A guide to technology-enhanced assessment and feedback. Retrieved from: https://www.webarchive.org.uk/wayback/archive/20140613220103
Hopkins, C. (2006). Making Things Our Own: The Indigenous Aesthetic in Digital Storytelling. Leonardo, 39(4), 341-344. Retrieved from http://www.jstor.org/stable/20206265
JISC (2007) Effective Practice with e-Assessment: An overview of technologies, policies and practice in further and higher education. Higher Education Funding Council for England (HEFCE). Retrieved from https://www.jisc.ac.uk/rd/projects/assessment-and-feedback
JISC (2009) Effective Practice in a Digital Age. Higher Education Funding Council for England (HEFCE). Retrieved from https://www.webarchive.org.uk/wayback/archive/20140613220103
JISC (2010) Effective Assessment in a Digital Age: A guide to technology-enhanced assessment and feedback. Higher Education Funding Council for England (HEFCE). Retrieved from https://www.jisc.ac.uk/rd/projects/assessment-and-feedback
Kim, J. (October 10, 2018). Is Technology Driving Educational Inequality? How digital learning concentrates higher ed privilege. Retrieved from https://www.insidehighered.com/digital-learning/blogs/technology-and-learning/technology-driving-educational-inequality
Lombardi, P. (2019). Instructional Methods, Strategies and Technologies to Meet the Needs of All Learners. Retrieved from https://granite.pressbooks.pub/teachingdiverselearners/chapter/universal-design-for-learning-2/
Lucas, A. (1996). Indigenous people in cyberspace. Leonardo, 29, (2), pp. 101-108.
Michel, T. (2019). An interview with Tim Michel [video]. In ETEC 521: Indigeneity and Technology. University of British Columbia.
McGee, P., & Reis, A. (2012). Blended course design: A synthesis of best practices. Journal of Asynchronous Learning Networks, 16(4), 7–22.
OER and Low Cost Materials at Penn State (2020). Benefits of Using OER. The Pennsylvania State University. Retrieved from https://oer.psu.edu/benefits-of-using-oer/
Rossity, J. (June 21, 2018). Assessment in a digital age: Rethinking multimodal artefacts in higher education. Retrieved from http://jenrossity.net/blog/?p=13227
Sharples, M. (May 10, 2019). To improve education – focus on pedagogy not technology. Retrieved from https://oeb.global/oeb-insights/to-improve-education-focus-on-pedagogy-not-technology/
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology & Distance Learning, 2, 3-10.
Stanford University. (n.d.) Learner variability. Retrieved from https://slc.stanford.edu/learner-variability
Stommel, J. (November 17, 2017). Critical Digital Pedagogy: a definition. Retrieved from https://hybridpedagogy.org/critical-digital-pedagogy-definition/