Online learning: engaging or isolating?

Abstract

Universal Design for Learning (UDL) is an effective and federally-mandated framework (IDEA 2004, HEOA 2008; Smith & Harvey, 2014) for engaging and educating students in ways that benefit all learners while providing a culture of inclusion for students in Special Education. UDL is often thought of as a technology-based framework but to be applied successfully, technology cannot be used in isolation. This paper explores the benefits and limitations of learning management system (LMS) technology like Schoology (K-12) and Canvas (post-secondary) that can support the realization of UDL principles. If used in isolation, however, LMS may limit or even obstruct learning and become yet another barrier to achievement. This paper explores the idea that human dialogue and collaboration beyond technology is required to fulfill UDL guidelines as well as academic objectives.

 Universal Design for Learning (UDL) Framework

Principles I, II & III and associated guidelines

CAST (2018). Universal design for learning guidelines version 2.2 [graphic organizer]. Wakefield, MA: Author.

Figure 1. The Universal Design for Learning (Cast 2011, Smith & Harvey, 2014) optimizes three groups of brain networks that play a primary role in learning: affective (via engagement), recognition (via representation) and strategic (via expression) – by taking into account learner diversity (Hall, Meyer & Rose, 2012).

Background

Palo Alto Unified School District, a fully-inclusive and UDL-integrated district, uses the LMS Schoology for K-12 engagement, teacher instruction (representation) and student expression. The benefits are clear. Students with Autism shine online – posting clever remarks on virtual discussion boards as well as editing and posting group projects on Schoology. LMS enables students with mild-to-moderate academic impairments to participate in dynamic ways with other students that were not always possible in person. These students could also “move at their own pace, engage in content at their own level and exhibit competency-based personal goals” while included in a general education classroom (Smith & Harvey, 2014). In Palo Alto, this opportunity to learn and express oneself via a computer is a definite plus for students in special education. What’s more, Palo Alto Unified balances these online experiences with in-class, in-person discussions and tactile learning experiences guided by excellent teachers who make the material exciting and relevant and who continually measure and clarify points of confusion in real time.

As California continues to suffer a severe shortage of special education teachers (Hale, 2015) and budgets shrink, districts may lean more on LMS technology than they should. LMS-based (Schoology and Canvas) education modules, which allow students to learn remotely and asynchronously at their own pace, don’t allow for in-person dialogue – where people gathered in a room are able to discuss and share what they know and therefore leverage their knowledge by integrating the ideas and influence of others. An increase in LMS learning should be balanced with, at minimum, live online discussions where students gather at the same time to share what they’ve learned with each other and their teachers. Because we all learn differently and have different perspectives, interacting with other human beings rounds out our perspective, clarifies gaps in our understanding and gives us ideas we may not have previously considered when studying academic concepts. In other words, our understanding and competency deepens when we add peer perspectives. Psychologist and social learning theorist Lev Vygotsky first touched on this idea during his observations of the development of speech and language – theorizing that when two people come together they actually have two different sets of understanding but after interacting, they walk away with both sets of understanding integrated and therefore their cognitive understanding and ability grows exponentially based on the number of human interactions a person has within a field of study. Interacting with a computer might seems like an ideal interaction but technology lacks the diversity of perspectives possessed by a group of people (Fulton & Kober, 2002). Even Artificial Intelligence (AI) often prompts us to share with it what we like so that the AI can provide us with more of the same type of content. At present, AI doesn’t introduce diversity and stretch a person’s perspective as much as a peer discussion and debate would. Technology also cannot accurately detect student confusion and develop individualized learning strategies as accurately as an in-person teacher can (Greer, Rowland & Smith, 2014). “Interestingly, LMS-based prepackaged modules are similar to those advocated by (psychologist and behaviorist learning theorist) B.F. Skinner in 1986. Skinner demonstrated that machine-driven modules have the potential to rapidly yield powerful learning outcomes, especially with superficial learning” (Eysink & de Jong, 2011; Smith & Harvey, 2014). This implies that deep, higher-level learning requires live human interaction.

LMS-based group projects completed remotely without live discussion do not mitigate the lack of in-person interaction but rather emphasize it because students do not open up and trust with an online, out-of-sync avatar the way they would with an in-person peer. As Learning Solutions magazine published, “In the learning environment, trust is built through positive experiences and familiarity – by getting to know others in the course – and a teacher must a find a way to recreate that experience to achieve high levels of engagement and achievement in online education” (Wilcoxon, 2011).  One of the greatest challenges for teachers - especially with older students - is building trust. Business research shows that online community may be an oxymoron – an impossible goal. Despite the advent of Skype and other diverse options for synchronous online conferences, Fast Company magazine published that online interactions do not build trust nor a sense of community among participants; they simply conserve energy (Vanderkam, 2015). Not meeting anyone in-person during an LMS-based course and not being able to read social cues (Dukes III & Koorland 2009; He, 2014) limits group work to its most functional form: trying to find each other online and just get the project done rather than giving deeper feedback that might be construed as offensive on a remote platform. Weekly online discussion boards on Canvas mirror Skinner’s concept of superficial learning.  In-person discussions tend to take place a few sentences at a time, evolving and moving from participant to participant in a rapid linear progression – not in longer paragraphs and multi-layer discussions that are more challenging to digest (Dukes III & Koorland, 2009). Responding to one other person’s post is not the same as listening to a group discussion by multiple peers nor does it qualify as a conversation where there is a back-and-forth dynamic and a real-time unfolding of understanding. In this capacity, an entirely LMS-based class “discussion” can feel like a barrier – a point of inflexibility and obstruction of Universal Design for Learning (UDL) rather than a delivery of its principles.

Education research reflects similar concerns about asynchronous learning – that the benefits of online learning unconstrained by time and space that allow people the flexibility to learn at their own pace causes varying degrees of loss of one’s learning community (Fulton & Kober, 2002). Loss of social interaction limits engagement, a UDL principle, as well as student ability to access a deeper understanding of subjects and diverse viewpoints (Fulton & Kober, 2002). The following research explores how the most effective implementation of LMS technology follows UDL guidelines and how tech developers and teachers might be trained to create optimal LMS-based education and therefore maximize student engagement and academic achievement.

Degree of Online Isolation

This paper will review three types of LMS-based learning and their degree of alignment with UDL principles: 1) blended learning where in-person instruction in a brick-and-mortar classroom is supplemented by tech resources such as an LMS; 2) hybrid learning where in-person classes meet a number of times over the semester but 30% or more of instruction takes place online on an LMS; and 3) entirely-online or virtual learning where the instructor and student never meet in-person but interact solely online via an LMS. (Savery, 2005; Greer et al., 2014)

“By 2019, 50% of all courses in grades 9-12 will be delivered in online learning environments” (Basham, Smith, Greer & Marino 2013). “Regardless of whether a teacher uses blended, hybrid or entirely-online virtual learning, the consistent challenge for teachers is to foster an online learning community, student involvement and focused dialogue” (Collier &Yoder, 2002) because “research shows that virtual education is most effective when interaction is at the heart of the instructional design and students are part of an active, sharing, learning community” (Fulton & Kober 2002; Collier & Yoder 2002). In order to achieve the third principle of UDL – multiple means of engagement – as well as seven of UDL’s nine guidelines, in-person interaction is key, especially student-teacher and student-student interactions (Dukes III & Koorland 2009). In fact UDL guidelines can be implemented with low- or no-tech environments (Hall, Myer & Rose, 2012) but the reverse is not always true. When educators attempt to achieve UDL requirements with technology alone, the technology can become yet another form of inflexible curricula that discriminates against some learners. “Even when online instructional quality is high, the rates of student dropouts are higher in virtual schools than in face-to-face courses because interaction between teachers and students is lower in quantity and quality and because some aspects of teaching such as studying people’s faces to gauge their understanding, giving immediate feedback and using classroom theatrics to engage students can’t be replicated online on an LMS” (Fulton & Kober 2002; He, 2014).  This is not just true for K-12 education. “Although online instruction has gained a sizeable and permanent foothold in post-secondary educational environments” (Dukes III & Koorland, 2009), “increasing numbers of students are not completing college once enrolled” (Tinto, 2002; Dukes III & Koorland 2009). An exception is a 2004 study that found that “timely feedback and consistent interaction with instructors leads to nearly 100% retention in online post-secondary programs” (Dahl, 2004; Dukes III & Koorland, 2014) and that “students reported greater satisfaction with their online course as their perception of the instructor’s availability increased” (Richardson & Swan 2003; Dukes III & Koorland 2009). It may be that because a college instructor has been vetted by a university, a student is more likely to automatically trust a professor’s avatar than that of an online, unknown classmate but the loss of peer-to-peer learning remains even if the teacher-student online interaction is high quality.

Along those same lines of in-person or perceived online interaction, drop-out statistics and graduation rates change dramatically when LMS-based curricula is used to support an in-person learning community rather than replace it. The Clayton Christensen Institute for Disruptive Innovation wrote 12 case studies about the impact of blended learning on traditional classrooms in 12 school districts nationwide. Four of the districts studied – Salt Lake City, Utah; Spokane, Wash.; Cookeville, Tenn.; and St. George, Utah – reported high dropout rates before the introduction of blended learning but a significant (8%-23%) increase in graduation rates after the implementation of LMS support in brick-and-mortar classrooms. All of the school districts studied – including the District of Columbia Public Schools and other districts in Illinois, Pennsylvania, Colorado, New York, South Carolina and Tennessee – reported extensive student gains in math and reading (The Clayton Christensen Institute, 2015). Although only 12 districts were studied, the upward trend of achievement gains and increased graduation rates across the board suggests that LMS technology is an important tool for the realization of UDL principles and academic achievement as long as it does not replace the in-person learning community. Conversely, “a lack of social presence may lead to a high level of frustration, a critical attitude toward the instructor’s effectiveness and a lower level of affective learning” (Hample & Dalliger, 1995; Baker, 2001; Savery, 2005; Gorsky & Blau, 2009). For success in virtual learning, a student must be self-motivated and able to work independently (Macdonald, Heap & Mason, 2001; Fulton & Kober, 2002; Kieser, Kollar & Schmidt, 2006; Dukes III & Koorland 2009) and use self-regulation (Kim & Bonk, 2006) and metacognition skills. (Bransford, Brown & Cocking, 1999). “Long periods of time can pass during virtual LMS learning, during which students may feel isolated and, without feedback, perceive that the instructor does not care and as a result are more likely to adopt a less engaged role themselves” (Savery, 2005). This loss of engagement may be compounded for Special Education students and at-risk, low-income students who often need extra but diverse means of instructor and peer support (Wilcoxon 2011; Smith, Polloway & Dowdy 2012; Smith & Harvey 2014).

LMS in Special Education

As predicted through the concept of disruptive innovation, the largest populations of students enrolled in K-12 online settings are traditionally identified as underserved… The largest year-to-year growth in online education was noted for students with disabilities… Virtual schools have averaged an annual growth rate of 15% (Basham et al., 2013).

Education research shows a disturbing trend: that districts are implementing virtual education LMS solutions for special education and at-risk, economically disadvantaged students (Basham et al., 2013; Greer et al., 2014) even though 85% of LMS developers are for-profit technology companies not federally mandated to use UDL nor any educational framework to guide LMS development (Clark 2009; Basham et al., 2013; Greer et al., 2014). Because tech developers lack expertise in education, they have an overly simplistic view of learner variability (Basham et al., 2013) and tend to focus on accessibility compliance rather than instructional flexibility (Smith & Harvey 2014). The result is that these special needs students receive LMS technology they can access – see, hear, touch – but the LMS does not provide “embedded supports, for example: for planning, goal setting, learning strategies, and management of resources vital to students with learning disabilities or language processing deficiencies” (Smith & Harvey 2014). LMS developers build one-size-fits-all learning tools that teach one concrete skill at a time, requiring mastery in that skill before moving to the next level of competency. This independent learning of increasingly difficult skills appeals to average and gifted students who can skip items they already know and work at their own pace. Special education students however can get stuck at one repeating level of the LMS without any embedded learning strategies or interventions to help them progress (Greer et al., 2014).

A federal study of the Kahn Academy, perhaps the world’s most acclaimed LMS which provides K-12 math and science education to 10 million students, found zero alignment with UDL principles in a survey of 478 Kahn lessons using a UDL Scan Tool developed by the Center for Online Learning and Students with Disabilities (Smith & Harvey 2014). In other words, although the Kahn Academy serves many students effectively, it does not serve all students and may even cause more harm than good to underserved populations (Basham et al., 2013).  The reason for this LMS limitation is easy to explain. Most LMS development companies subscribe to one specific theory of learning, eg: the constructivist theory or behaviorist theory (Papert, 1980, 1994; Papert & Harel, 1991; Skinner, 1986; Basham et al., 2013) – bypassing decades of scientific research that now recommends an integrated approach to learning theory and application (Gleason, 2013). In short the LMS developer makes a simplistic assumption that all students learn the way he learns. UDL captures the reality of learner variability (Basham et al., 2013) – that students are vastly more complex entities than any one learning theory can capture (Dukes 2009; Gleason, 2013). Unlike mass produced technology, every human being is as unique as a fingerprint. An exceptional teacher recognizes that and is able to figure out the right combination of tools and strategies to address each student’s needs – technology being only one of those tools.

Some examples of unique obstacles faced by diverse learners are 1) needing specific assistive technology not included in an LMS, 2) lack of education or lack of background or cultural knowledge, 3) lack of English fluency among English Learners or students with language impairments that limit the ability to understand text or spoken language without social cues, 4) lack of pragmatic social skills that prevent students with Autism from understanding implied humor on discussion boards, 5) lack of self-regulation and metacognition in students with cognitive disabilities and attention deficits (Dukes III & Koorland, 2009) as well as language and literacy delays, and learning disabilities like processing challenges, cognitive delays and dyslexia (Smith & Harvey 2014).

The value of in-person collaboration and interaction in learning communities to help all learners achieve success is woven throughout UDL’s three principles and corresponding guidelines (Hall, et al., 2015). The following UDL guidelines list key aspects of instruction flexibility that virtual learning lacks: multiple sensory modalities eg: touch, taste, smell (UDL #1), multiple means of engaging in language (UDL #2), multiple means for comprehension, modeling and mentoring (UDL #3), options for physical actions (UDL #4), multiple options for communication (UDL #5), creating a safe learning environment (UDL #7), fostering collaboration, community and increasing mastery-oriented feedback (UDL #8), managing anxiety and social aspects of lessons (UDL #9) (Hall, et al., 2015) and creating an environment that promotes interaction and communication among students and between students and faculty (Universal Design for Instruction #8, Dukes III & Koorland, 2009). Ironically technology that does not incorporate this flexibility puts the very students it is designed to help at a disadvantage.

When used alone, mass-produced LMS solutions that do not incorporate UDL deliver only superficial personalization of content (Smith & Harvey 2014) and miss an opportunity to identify barriers to learning (Dukes III & Koorland 2009) to become effective tools for struggling students. However “blended classrooms present an opportunity to proactively consider and address the needs of diverse learners” (McGuire & Scott 2006; Dukes III & Koorland, 2009) by giving students a variety of both online and in-person modes of representation, expression and engagement or “flexible content and instructional delivery with the potential to transform student outcomes” (Smith & Harvey 2014). Blended learning aligns with UDL Guideline 8, which recommends fostering collaboration and community and an increase of mastery-oriented feedback to motivate students to sustain their effort and persistence (Hall, et al., 2015).

Recommended Training

An online learning environment should connect the students with meaningful experiences, provide the appropriate climate for growth and understanding, give the students the ability to control their own learning, offer an engaging curriculum that uses evidence-based teaching practices, and ensure a learning community that is caring. Simply thinking of online education as being driven by technology, rather than instructional design, limits the ability to accomplish the desired outcomes.  (Basham et al., 2013)

The challenge of training human beings in effective LMS application is two-fold: educators as well as LMS developers must be trained in the benefits of flexible learning strategies as well as encouraged to work together as a team across industry and education to align new technology with decades of education research (Basham et al., 2013; He, 2014). Obstacles to this two-fold goal involve districts’ teacher development priorities – most teachers are expected to master technology independently (He, 2014) – and the speed of technological development, which dwarfs the methodical and slow-to-change field of educational research (Basham et al., 2013). Technology companies will have to recognize that they are not experts in education and involve educators in LMS development voluntarily, or the federal government should require LMS compliance with UDL guidelines in the same way it requires accessibility compliance.

Conclusion

Until all forms of virtual education are fully aligned with UDL principles, a blended learning model is clearly ideal for K-12 districts because it provides the benefits of in-person learning communities while tapping LMS technology for UDL support in flexible instruction, expression and engagement catered to individual students (Basham et al., 2013). At the university level, students commuting long distances would benefit from implementing a hybrid learning approach. By making all courses neither solely virtual nor solely in-person but instituting hybrid courses across the board  - delivering a mix of in-person classes and LMS-based classes for every course, universities can ensure that all students benefit from both in-person learning communities and asynchronous technology in every course. The in-person classes can be used to establish trust and collaboration among students as well as a bond with the instructor and the remaining LMS-based classes can provide multiple learning modes and reduced commute hours. This would conserve both human energy and gasoline without sacrificing higher-level social learning and the inclusive model of education. The recent COVID-19 pandemic Shelter in Place Orders introduced the education world to a new technology Zoom that, pending education research, seems to create a bridge between the virtual and in-person worlds, allowing classes of teachers and students to learn and discuss topics together in real time. While students who are at-risk or on special education tracks may need dramatically smaller groups and more teacher interaction to access the same discussion online, it could be argued that technology like Zoom that mimics in-person learning environments by providing eg: whiteboard and share-screen functions for multiple means of representation, engagement and expression and live interaction with a teacher and peers is the next-step toward UDL-aligned virtual learning. If Artificial Intelligence (AI) starts to take on live teacher roles, it must be programmed to stretch students toward diverse-and-complex rather than uniform-and-superficial perspectives and be able to detect the appropriate learning strategy needed when a student is stuck. Without some real-time human collaboration, however, LMS-based instruction threatens to become just as standardized, rigid and ineffective for learners as pre-UDL models of education – and far more isolating.

References

Baker, J. D. (2001). The effects of instructor immediacy and student cohesiveness on affective and cognitive learning in the online classroom [Doctoral dissertation]. Dissertation Abstracts International, 62, 06. 2081 UMI No. 3018333. Regent University.

Barbour, M. K., & Reeves, T. C. (2009). The reality of virtual schools: a review of the literature. Computers & Education, 52, 402–416. Retrieved from researchgate.net

Basham, J., Smith, S., Greer, D. & Marino, M. (2013) The scaled arrival of K-12 online education: emerging realities and implications for the future of education. Journal of Education, Vol. 193, No. 2, p. 51-59 University of Central Florida.

Bransford, J. D., Brown, A., & Cocking, R. (Eds.). (1999). How people learn: mind, brain, experience and school. Washington, DC: National Academy Press.

Clark, R. E. (2009). Translating research into new instructional technologies for higher education: the active ingredient process. Journal of

Computing in Higher Education, 21, 418.

Clayton Christensen Institute for Disruptive Innovation & Evergreen Education Group. (2015). Case Study: Blended learning success in school districts, http://www.christenseninstitute.org/publications/proof-points/

Collier, C. & Yoder, M. (2002). Successful online discussion and collaboration: techniques for design and facilitation, in D. Willis, J. Price & N. Davis (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference (pp. 2351-2355), Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).

Dahl, J. (2004). Strategies for 100 percent retention: feedback, interaction. Distance Education Report, 8(16), 1,6-7.

Dukes III, L. & Koorland, M. (2009). Making blended instruction better: integrating the principles of universal design for instruction into course design and delivery. Action Teach Education Vol. 31 No. 1, University of South Florida, St. Petersburg.

Eysink,T. H., & de Jong,T. (2011). Does instructional approach matter? How elaboration plays a crucial role in multimedia learning. Philadelphia, PA: Routledge.

Fulton, K. & Kober, N. (2002). Preserving principles of public education in an online world, Center on Education Policy, Washington, D.C.

Gorsky, P., & Blau, I. (2009). Online teaching effectiveness: a tale of two instructors. International Review of Research in Open and Distance Learning, 10(3).

Greer, D., Rowland, A. & Smith, S. (2014) Critical considerations for teaching students with disabilities in online environments. Teaching Exceptional Children, Vol. 46, No. 5, pp. 79–91.

Gleason, J. (2013) The Development of Language, 2013, Pearson Education, Eighth Edition, Boston University HEOA: Higher Education Opportunity Act of 2008

Hall T., Meyer A. & Rose D. (2012). Universal design for learning in the classroom: practical applications, The Guilford Press, London.

Hample, D., & Dallinger, J. M. (1995). A Lewinian perspective on taking conflict personally: revision, refinement, and validation of the instrument. Communication Quarterly, 43, 297-319.

Hale, L. (2015). Behind the Shortage of Special Education Teachers: Long Hours, Crushing Paperwork, NPR Public Radio, KQED San Francisco. http://www.npr.org/sections/ed/2015/11/09/436588372/behind-the-shortage-of-special-ed-teachers-long-hours-crushing-paperwork?

He, Y. (2014) Universal design for learning in an online teacher education course: enhancing learners' confidence to teach online. MERLOT Journal of Online Learning and Teaching. Vol. 10, No. 2. University of North Carolina at Greensboro.

IDEA: Individuals with Disabilities Act of 2004

Kieser, A., Kollar, K., & Schmidt, J. (2006). E-learners. From http://iit.bloomu.edu/Spring2006_eBook_ files/chapter1.htm

Lips, D. (2010). How online learning is revolutionizing K-12 education and benefiting students. Heritage Foundation. Retrieved from http://www.heritage.org/research/reports/2010/01/how-online-learning-is-revolutionizing-k12-education-and- benefiting-students

Lowenthal, P. R. (2009). Social presence. In P. L. Rogers, G. A. Berg, J. V. Boettcher, C.

Howard, L. Justice, & K. D. Schenk (Eds.), Encyclopedia of distance and online learning (2nd ed., pp. 1900- 1906). Hershey, PA: Information Science Reference. doi:10.4018/978-1-60566-198-8. ch 280

Macdonald, J., Heap, N., & Mason, R. (2001). "Have I learnt it?" Evaluating skills for resource based study using electronic resources. British Journal of Educational Technology, 32(4), 419-434.

McGuire, J. M., & Scott, S. S. (2006). An approach to inclusive college instruction: universal design for instruction. Learning Disabilities: A Multidisciplinary Journal, 14, 21-31.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies [Technical Report]. Washington, DC: US Department of Education.

Papert, S. (1980). Mindstorms: children, computers, and powerful ideas. New York, NY: Basic Books.

Papert, S. (1994). The children’s machine: rethinking school in the age of the computer. New York, NY: Basic Books.

Papert, S., & Harel, I. (1991). Situating constructionism. Constructionism, (pp. 193-206). New York, NY: Ablex Publishing Corporation Retrieved from http://www.papert.org/articles/SituatingCon- structionism.html

Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students' perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88.

Russo, T. C., & Campbell, S. W. (2004). Perceptions of mediated presence in an asynchronous online course: Interplay of communication behaviors and medium. Distance Education, 25(2), 215-232. doi:10.1080/0158791042000262139

Savery J., Be vocal: characteristics of successful online instructors, Journal of Interactive Online Learning, Volume 4, Number 2, The University of Akron, 2005

Skinner, B. F. (1986). Programmed instruction revisited. The Phi Delta Kappa, 68(2), 103-110.

Smith, S. & Harvey, E. (2014) K-12 online lesson alignment to the principles of universal design for learning: the Khan Academy, Open Learning. The Journal of Open, Distance and e-Learning, 29:3, 222-242, DOI: 10.1080/02680513.2014.992402

Smith, T. E. C., Polloway, E. A., Patton, J. R., & Dowdy, C. A. (2012). Teaching students with special needs in inclusive settings (6th ed.). Upper Saddle River, NJ: Pearson Education.

Tinto, V. (2002). Enhancing student persistence: Connecting the dots. Paper presented at "Optimizing the Nation's Investment: Persistence and Success in Postsecondary Education," Madison, WI.

Vanderkam, L. (2015, Sept. 30) The science of when you need in-person communication, Fast Company magazine, From: http://www.fastcompany.com/3051518/the-future-of-work/the-science-of-when-you-need-in-person-communication

Wilcoxon, K. (2011, Oct. 3), Building an online learning community. Learning Solutions magazine, Santa Rosa, California. From: http://www.learningsolutionsmag.com/articles/761/building-an-online-learning-community

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