Online Educational Multimedia: Designing for the 21st-Century Mobile Learner
Thomas Sendgraff, Teachers College, Columbia University, ths2129@tc.columbia.edu
Abstract: The popularity of online education and mobile devices continues to proliferate. Online courses and its supporting multimedia content can be accessed almost anywhere and at any time. Learners utilize their mobile devices in a variety of situated environmental contexts. This has design implications around context and how instructional and multimedia designers integrate supportive multimedia. There is currently minimal research and evidence of multimedia designers following research-supported design choices. However, leading theories have been compiled into a new and comprehensive framework. The framework supports thoughtful knowledge and recognition of how to produce online multimedia artifacts that best support learning goals. The four aspects are active learning, Cognitive Theory of Multimedia Learning, student sense-making, and situated environmental context.
Keywords: Active learning, Cognitive Theory of Multimedia Learning, multimedia, situated environmental context, student sense-making
Literature review
Instructional designers must think purposefully about how technology supports learning. Often, the problem of first thinking about the platform (or overall e-learning) that delivers the instruction on devices (e.g., mobile app, tablet, and computer) is considered before examining the overall context of why this matters for learning in the first place (at home, commute, at work, cafe, etc.) (Bonk, Lee, Kou, Xu, & Sheu; Hibbert, 2015, 2017; Horn, 2019; Vasudevan, Schultz, & Bateman, 2010). The physical contexts where and when learners access their course’s artifacts expands through mobile device utilization. What does this mean for 100% online matriculated higher education learning using multimedia to support learning goals via multiple platforms and contexts? There is currently an under-researched gap in considerations on the construction of multimedia artifacts to fit the needs of online adult learner’s interdependent cognitive load and situated environmental contexts (Bo & Fu, 2018; Choi & Johnson 2005). Many designers may lack the knowledge and recognition skills needed to fully understand how to design and utilize multimedia to support learning goals.
The online education industry is currently experiencing a “gold rush” with $107 billion in 2015 (Hibbert, 2017, p. 12). Bonk et al. (2014) argue that “humans are increasingly migrating to online environments for their learning needs” (p. 362). In 2019, one-third of college students took at least one online course. Also, the enrollment numbers are substantial when solely examining graduate education enrollment. For example, “more than one-quarter of all master’s students are learning exclusively online” (Horn, 2019, p. 82). The number of online learners will expand into the digital frontier of the online education industry; thus, leaving room for exploration around multimedia design and design-based research possibilities.
Learning theories and minimal research do exist that collectively can be utilized to develop a deeper understanding of multimedia artifact’s relevance to the online learner context. Prior research findings stem from deep theoretical and pedagogical considerations blending cognitive load reduction and social constructivism at its core (Sweller, 1988; Vygotsky, 1968). The prior research findings provide evidence to construct a framework consisting of intersectionalities between active learning, Cognitive Theory of Multimedia Learning, student sense-making, and situated-context (Brame, 2015; Brown, Collins, & Duguid, 1989; Hibbert, 2015, 2017; Jonassen, Howland, Marra, & Crismond, 2011; Mayer, 2001) (see framework 1). The four key features culminate in a useful framework to assist in designing multimedia for online learners. The benefit of this framework is it promotes thoughtful knowledge and guidance on how to produce online multimedia artifacts. Overall, the framework supports situated environmental context and multimedia design to maximize support for learning goals.
Framework 1: The key considerations for designing multimedia artifacts to support an online learner’s goals.
Active learning
Active learning is essential for eliciting student’s engagement and motivation. Jonaseen et al. (2011) argue that active learning through the practice of constructing meaning with schemas is one important aspect of meaningful learning. Conaway & Zorn-Arnold (2015) discuss how adult learners drawing on schemas become motivated to learn. Adult learners are aware of gaps in their knowledge and are eager to learn. Brame (2015) argues that multimedia artifacts lacking engaging participation will promote passive interactions; thus, the opportunity for learning with supportive multimedia will minimize. Choi & Johnson (2005) argue that multimedia can be naturally attention-grabbing; however, passive interactions will not maximize behavior and cognitive processing capable of supporting learning goals. Schwart & Hartman (2005) discuss how video multimedia is superb at capturing attention and setting the stage for objectives and goals. Brame argues that active learning can be considered as an artifact explicitly setting the stage for supporting homework assignments and activities. For example, flipped classroom or anchored-based learning that utilizes video context to anchor meaningfully active discussions and reflections. Also, educational games can draw on learner’s active participation, while integrating “stealth assessments, which are embedded prompts throughout gameplay (Shute, 2011). Designing multimedia with strategies of active learning can harness its potential as an engaging and motivating tool with the intention to reduce passive learning.
In addition, multimedia setting the stage for active learning must acknowledge a student’s cognitive load and environmental context. Bonk et al. (2015) discuss quantitative survey analysis of online student’s usage of mobile devices and physical locations. The findings shed light on devices based on the student’s answers. The majority of learners said they used laptops at home; however, around 40% utilized mobile technology in a variety of public locations. A few locations included work, library, cafes, public commute, etc. This means that learners may face constraints of time and cognitive load in the surrounding space (e.g. noise, movement, etc.). Hibbert (2015) argues that the environment plays a key role in learner’s active participation. For example, adult learners who are on break at work may experience less time to complete multimedia artifacts, such as videos and games; thus, active learning is reduced if artifacts are lengthy and do not specify explicit recommendation of note-taking or linkage to assignments and activities. Guo, Kim, & Rubin (2014) discuss their mixed methodology research on the intersectionalities between engagement and length of video. The findings shed light on how artifacts exceeding 6 minutes saw a drop in watch time. A learner’s interest decreased, which is arguably due to disinterest and cognitive load. Horn (2018) argues that learners can become quickly boring. Brame (2015) supports Guo et al.’s findings and argues that less information can be committed to long-term memory when being exposed to too much information. Designing active learning requires thinking about learner’s environmental contexts and how the length of multimedia impacts cognitive load. Multimedia supporting learning goals will minimize without these design considerations. To ensure active learning there must be consideration of adult learner’s limited time and attention by creating shorter multimedia (6 minutes or shorter) segmented and linked to tasks.
Cognitive theory of multimedia learning
Richard Mayer (2001) developed the leading CTML framework for multimedia design aiming at cognitive load reduction. The framework consists of twelve principles to increase the potential for multimedia tools to assist in knowledge retention and learning goals. The principles are rooted in the cognitive psychology of Cognitive Load Theory (CLT). Sweller (1988) developed CLT to explain the process of how intrinsic short-term memory became committed to long-term germane load memory. Distracting information will work as extraneously unneeded information decreasing the process of intrinsic memory to germane load. Germane load is long-term retention of information in categorical structures, such as schemas; thus, multimedia must be purposeful and its design to promote cognitive processing and elimination of unnecessary information. CMLT draws on CLT to provide design principles aiming to support active learning and decrease the cognitive load. However, CMLT and CLT don’t necessarily discuss motivation or account for online student’s situated environmental contexts.
In addition, Jiang, Renandya, & Zhang (2017) conducted a mixed methodology research drawing on Mayer’s Cognitive Theory of Multimedia Learning (CTML). The study tested Mayer’s twelve principles of multimedia design for effects on reducing cognitive load. The study mentions an observable discrepancy of multimedia designers’ basing choices on instinct rather than researched principles. The study produced findings suggesting the inclusion of CTML has positive effects on student’s overall online course satisfaction. The study also found that instructor and student perceptions of multimedia can greatly differ. Also, CTML principles can be utilized to help frame questions for survey analysis for instructors and learner’s experiences of multimedia artifacts. For example, Mayer’s (2001) coherence principle may ask learner’s thoughts about distracting information, such as if graphics supported mathematical word problems. Paolo, Wakefield, Mills, & Baker (2017) discuss how conducting survey analysis after learner’s view multimedia can provide feed-forward evidence. The information can be useful for improving future multimedia artifacts.
Student sense-making
Learner’s interpretations and motivations to learn with various multimedia tools can greatly vary. Hibbert (2015) conducted qualitative talk-through analysis on online graduate students’ experiences with multimedia artifacts. Hibbert argues that multimedia designers think more about crafting meaning and messages, rather than how it may be interpreted. For example, CMLT discusses only design principles to minimize extraneous load. Hibbert explores the learner’s sense-making experience of instructional video content. Her findings shed light on how learner’s “blurred” all multimedia artifacts into one experience. She found that students did not differentiate between instructional video, presentation software, or live video conferencing. This means that multimedia could easily blur into and support active learning tasks and goals.
Sense-making is rooted in social semiotics framing the symbolic meaning behind each mode of communication. Different combinations of modes can increase or decrease learning potential. Modes are packages of affordances useful for considering how multimedia can be produced and interpreted. Multimedia is constructed with modes and different combinations can elicit interests and capability to “increase meaning-making potential” (Hull & Nelson, 2005, p. 225). Paolo et al. (2017) discuss how multimodality assists in mental picturing and connecting schemas; thus, multimodality can increase the potential for prior experience to help make sense of new information. Different modes can also present complex information to novices (without rich domain-knowledge prior experience) to gain problem and pattern recognition (The Cognition and Technology Group at Vanderbilt, 1990). McLuhan & Fiore (1967) discuss how mediums are the tools responsible for communication mode interactions. 21st-century tools include mobile devices, which influence how and what modes can be utilized for sense-making. For example, a video contains visual and gesture modes, while podcasts do not.
Hibbert (2015) discusses the intersectionalities of multimodality and learner interpretations. She suggests that designing for the variances of learner’s sense-making interpretations means considering the audience and learner agency. Instructional designers commonly construct learner profiles to maximize learning outcomes (Smith and Ragan, 2005). However, multimedia is constructed in advance (before learner profiles can be constructed) and then delivered to learners. Hibbert mentions that other characteristics can be considered, such as the institution’s demographics, majors, and general student expectations. Horn (2019) argues that multimedia reflective of the learner’s interests with engaging story content can elicit motivation. For example, visuals (video) or audio (podcast) including well-known professionals or alumnus in a career field relevant to a major. Also, learners expect quality video and confident gestural mode presenters to increase sense of credibility. Learners also expect multimedia to allow interaction and freedom. Sherer & Shea (2011) argue that 21st-century learners are used to interactive multimedia from living in a web 2.0 world. For example, Hibbert (2017) discusses how allowing control of video media players can elicit motivation.
Sense-making can be a difficult phenomenon for an instructor to assess. There are options for how to measure learner’s performance linked with multimedia to support learning goals. Jonassen et al. (2011) argue that any ill-structured tasks with multiple answers will benefit from the use of a rubric. A rubric can detail explicit expectations on how learners should interact and use multimedia to support tasks. For example, a learner with no directions or expectations will have no guidance on how to interpret content. Another form of assessment is learning management systems (LMS) analytic reports. Lockyer, Heathcote, & Dawson (2013) discuss how the reports can provide a “digital footprint” tracking a student’s activity. For example, whether a student selected a video link to watch for an anchored discussion. A third assessment is stealth assessment in games, such as prompts that encourage active learning and provide instant feedback (Shute, 2011). A fourth assessment form is through instructor-guided peer-feedback. Paolo et al (2017) and Saltan, Ozden, & Kiraz (2016) discuss how peer evaluation can synergize sense-making interpretations. Peer evaluation can be useful for large classrooms and seeing multiple perspectives.
Situated environmental context
Situated environmental context is a culmination of social constructivism and situated cognition leading theories. The theories suggest that learning is beyond stages of cognitive development and includes social, cultural, and physical environmental contexts (Brown et al., 1989; Vygotsky, 1967). Choi & Johnson (2005) and Tessmer & Richey (1997) argue that learning is based on an inescapable context. For example, everyday situations and medium tools cannot be isolated from how students interpret and learn information. Designers must consider how to accommodate for a learner’s environment, such as where and how they interact with multimedia via mobile devices.
In addition, the environmental setting while accessing learning platforms strongly alters the nature of learning. Tessmer & Richey (1997) argue that situated environmental context influences performance, such as work, lab, or in-person classroom. This study came before the advancement of mobile devices, such as laptops, cellphones, and iPads. However, the theoretical implications of environmental influences arguably still apply in the 21st century, but have expanded to include cafes, commuting, etc (Bonk et al., 2015). Tessmer & Richey also discuss how the intersectionalities between the nature of the learning and environment impact performance. Motivated students are less affected or vulnerable to physical pain, such as uncomfortable sitting arrangement. While learners tasked with problem-solving assignments may be more vulnerable to sounds, such as noisy cafes, commuting, and work breaks; thus, cognitive load can be induced from different situated environment contexts. A solution for designers considering situated environmental context is to provide explicit descriptions with multimedia artifacts. For example, mentioning how different physical settings could impact their experience of multimedia and learning goals. Learners can gain awareness of how the nature of different environments can be a distraction. Essentially, designers cannot stop or control learners from where, when, and how online course content is accessed; however, accommodation can always be included to support learners by explicitly addressing different environmental settings.
Conclusion
The advancements of mobile devices and online education platforms create design implications. The way students think, learn, and interact is different within an online space versus on-site or hybrid/blended courses. Online learners are adults who are physically separated from an on-site social presence with instructors and peers (Paolo et al., 2017). Online learner’s physical environments are their choice. The learners can access information in different settings across their busy lives. Bonk et al. (2015) provided quantifiable evidence to support where and how online learners access learning platforms via mobile devices across physical contexts.
There is a large opportunity for design-based research to be conducted on multimedia in software mediated education (Hoadley, 2018). A multimedia artifact is a useful tool that can be harnessed for supporting learning goals. However, designers not accommodating for situated environmental context will not support learners. Future research needs to be conducted to provide an explicit understanding between how mobile devices, multimedia, and situated environmental context impacts learning. Designers and researchers could test learning outcomes from students in various settings experiencing different types of assignments. A mixed methodology of quantified scores and descriptive nature of learner’s experiences could provide insight into: what does this mean for 100% online matriculated higher education learning using multimedia to support learning goals via multiple platforms and contexts?
Currently, a framework does not exist to assist in designing multimedia for supporting online student’s learning in different physical settings. There is minimal research that does exist. The research has been compiled into a framework consisting of active learning, Cognitive Theory of Multimedia Learning, student sense-making, and situated-context. The framework is useful for instructional and multimedia designers who wish to promote multimedia to support learning goals. Multimedia can best support learning if its design follows the framework to assist 21st-century online learners (see framework 1).
References
Bonk, C., Lee, M., Kou, X., Xu, S., & Sheu, F.. (2015). Understanding the self-directed online learning preferences, goals, achievements, and challenges of MIT opencourseware subscribers. Educational Technology & Society. 18. 349-365.
Brame, C.J. (2015). Effective educational videos. Retrieved 3/31/2020 from http://cft.vanderbilt.edu/guides-sub-pages/effective-educational-videos/.
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.
Choi, H. J., & Johnson, S. D. (2005). The effect of context-based video instruction on learning and motivation in online courses. American Journal of Distance Education, 19(4), 215-227.
Conaway, W., & Zorn-Arnold, B. (2015). The keys to online learning for adults: The six principles of andragogy. Distance Learning, 12(4), 37+.
Guo, P. & Kim, J. & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. 41-50.
Hibbert, M. (2017). Blurred experiences: The undefined contours of student learning in online environments. Journal of Interactive Online Learning, 15(2), 92-106.
Hibbert, M. C. (2015). Student experiences with instructional videos in online learning environments. Teachers College, Columbia University.
Hoadley, C. (2018). A short history of the learning sciences. In International Handbook of the Learning Sciences, 1-23.
Horn, M. B. (2019). Online learning goes hollywood: Using video storytelling to motivate learning. Education Next, 19, 82+.
Hull, G. A., & Nelson, M. E. (2005). Locating the semiotic power of multimodality. Written Communication, 22(2), 224–261.
Jiang, D., Renandya, W., & Zhang, W. (2017). Evaluating ELT multimedia courseware from the perspective of cognitive theory of multimedia learning, Computer Assisted Language Learning, 30:7, 726-744,
Jonassen, D., Howland, J., Marra, R., and Crismond, D. (2011) Meaningful learning with technology. Boston: Pearson.
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist, 57(10), 1439–1459.
Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.
Mcluhan, M. & Fiore, Q. (1967). The medium is the massage. Gingko Press Incorporated.
Ögren, M., Nyström, M. & Jarodzka, H. (2017) There’s more to the multimedia effect than meets the eye: is seeing pictures believing?. Instr Sci 45,. 263–287.
Paolo, T. D., Wakefield, J. S., Mills, L. A., & Baker, L. (2017). Lights, camera, action: Facilitating the design and production of effective instructional videos. Tech Trends, 61(5), 452-460.
Saltan, F., Ozden, M., & Kiraz, E. (2016). Design and development of an online video enhanced case-based learning environment for teacher education. Journal of Education and Practice. 7. 14-23.
Schwartz, D. L., & Hartman, K. (2007). It is not television anymore: Designing digital video for learning and assessment. Video research in the learning sciences, 335-348.
Sherer, P. & Shea, T. (2011). Using Online video to support student learning and engagement. College Teaching, 59(2), 56-59.
Shute, V. J. (2011). Stealth assessment in computer-based games to support learning. In S. Tobias & J. D. Fletcher (Eds.), Computer games and instruction (pp. 503–524). Charlotte, NC: Information Age Publishers.
Sweller, J. (1988). Cognitive load during problem-solving: Effects on learning. Cognitive Science, 12(2), 257-285.
Vasudevan, L., Schultz, K., & Bateman, J. (2010). Rethinking composing in a digital age: Authoring literate identities through multimodal storytelling. Written Communication, 27(4), 442–468.
Vygotsky, L.S. (1978). Mind in society. Cambridge, MA: Harvard University Press.
Zull, J. (2002). The art of changing the brain. Virginia: Stylus Publishing.
Welcome 