universal design for learning (UDL)
The Center for Applied Technology has defined universal design for learning as: “Multiple means of representation, to give learners various ways of acquiring information and knowledge; Multiple means of expression, to provide learners alternatives for demonstrating what they know; and Multiple means of engagement, to tap into learners’ interests, offer appropriate challenges, and increase motivation” (http://www.cast.org/research/index.html)
Applications of universal design in architecture, electronics and civil engineering have had great success in making the world more accessible to all users. Most recently, it has been used extensively to make the world-wide-web accessible to all users (Roberts, 2004; Burgstahler, 2002; IBM, 2005; Pearson & Koppi, 2003). While universal design has been successful in making online courses more accessible in the realms of physical and sensory needs, the design method doesn’t fully address the need for varied learning needs. …
Universal design for learning (UDL) has been promoted over the past decade as a way to make learning accessible to more users, based on an array of choices made by the learner (Hall, Strangman & Meyer, 2005). Widely recommended as a tool for differentiation of instruction in K-12 classrooms, only recently have a few studies begun to discuss its use in postsecondary settings (Field, Sarver, & Shaw, 2003).
Solomon and Felder online assessment at http://www.engr.ncsu.edu/learningstyles/ilsweb.html (Solomon & Felder, 1999) and report their summarized results. Participants were asked to report on four axes of learning styles. They could be at either end of the axis for each pair, or in the middle, showing no preference for either end. The four pairs were (a) reflective vs. active; (b) sensing vs. intuitive; (c) visual vs. verbal; and (d) sequential vs. global.
studies that have examined the relationships between personality preferences, learning styles and instructional methods used in online courses, making recommendations based on their findings (Irani, Telg, Scherler, & Harrington, 2003; Higgins, 2002; Kim & Schniederjans, 2004; Jenkins & Downs, 2003). In some cases, there have been surprising results when applying MBTI types to internet activity preferences (Desmedt & Valcke, 2006; Amichai-Hamburger, Wainapel, & Fox, 2003, Bonebrake, 2002; Nussbaum et. al, 2004; Contreras, 2004)
http://jolt.merlot.org/vol3no2/engleman.htm
Learn more….
surprising results when applying MBTI types to internet activity preferences (Desmedt & Valcke, 2006; Amichai-Hamburger, Wainapel, & Fox, 2003, Bonebrake, 2002; Nussbaum et. al, 2004; Contreras, 2004)
Desmedt, E., & Valcke, M. (2006). Mapping the learning styles “jungle”: An overview of the literature based on citation analysis. Educational Psychology, 24(4) 445-464.
Amichai-Hamburger, Y, Wainapel, G, & Fox, S. (2002). “On the internet, no one knows I’m an introvert”: Extroversion, neuroticism, and internet interaction. Cyberpsychology and Behavior, 5(2), 125-128.
Nussbaum, E., Hartley, K., Sinatra G., Reynolds, R. & Bendixen, L. (2004). Personality interactions and scaffolding in on-line discussions. Journal of Educational Computing Research, 30(1&2), 113-137.
Contreras, C. (2004). Predicting computer self-confidence from demographic and personality variables and computer use. Quarterly Review of Distance Education, 5(3), 173-181.