Twas the night before Christmas and all through the house, nothing was stirring not even a mouse…except the sound of my fingers tapping away on the keyboard that is…
Today’s blog post is a follow on from yesterday, not only on the theories of learning design, but the learners perceptions of learning design and how this may impact on their motivation to learn.
So far much consideration has been given to the academic viewpoint on the creation of learning design, in order to balance the review the viewpoint of the learner’s perception of learning design must be given.
With the developments of online learning materials, and wider access to unlimited internet with the emergence of broadband, it has now been possible more than previously to create learner-centred online learning experiences of materials, tasks and activities to fit learner styles and preferences (Bonk, Wisher & Lee, 2003). The access to learning materials doesn’t even need to be linear with the ability to dip in and out of resources via online search engines, with learners selecting the elements that they wish to learn, which may not necessarily be a course as a whole. This slightly more modular and disjointed approach can have ramifications on a learning design with learners cherry picking the ‘best’ elements of a course to suit their needs, with the additional possibility of the learner accessing these elements in a different order to what the learning designer intended.
‘Those students who may not have developed appropriate strategies for self-regulation drop the course; as a consequence, online courses have been associated with much higher rates of attrition than traditional ace-to-face courses’
(Summers, Waigandt & Whittaker, 2005)
Literature by Aragon, Johnson & Shaik (2002), Boyd (2004), and Meyer (2003) suggest that there may only be certain types of learner that can successfully learn in an online environment. There is a consistency within the literature that infers that learners of an independent and self-regulatory nature coupled with the motivation and belief that they can learn effectively and successfully online are more likely to complete their online studies (Meyer, 2003).
A learning style model ‘classifies students according to where they fit on a number of scales pertaining to the ways they receive and process information’ (Felder & Silverman, 1988), however at what point are learners given the opportunity to ascertain what learning style they have or the further opportunity to develop, change, or enhance their learning style to increase successful completion? Learning design is an emergent field for a informal online learning, with many focusing on learner-centred learning, however little attention seems to have been given to the learner understanding that they are at the centre of the learning, and identifying the most suitable learning for them.
‘…those who lack the skills for self-regulation and a deeper understanding of their preferred learning styles may find the online environment difficult and become confused.’
Studies by Terrell (2002) suggest that students with an indication of Kolb’s (1984) AC (Convergers and Assimilators) had a stronger preference for online learning and more likely to be successful in its completion than students displaying a CE (Divergers and Accommodators). Aragon et a; (2002) also found significant difference between the learning styles of online learners with that of their traditional face-to-face counterparts, with the online learners being more Convergers and the classroom learners being Assimilator in learning style, adding that in both environments it is possible to learn as effectively regardless of learning style preferences acorss motivation, cognition, and task engagement activities. Manochehr (2006) however, stated that learning styles within a traditional setting are irrelevant, but with online learning it is very important, with Assimilator and Converger learning styles successfully achieving in the online environment, and Diverger and Accommodator more successful in the traditional environment.
This draws back to the earlier point, that though academics may have identified these learning styles and equated them to successful learning, it may not have been the same for the learner have the ability for self-identification and matching to a subsequent suitable learning environment.
According to Johnson and Aragon (2003) ‘powerful online environments’ need to comprise of the following:
- Address individual differences
- Motivate the student
- Avoid information overload
- Create a real-life context
- Encourage social interaction
- Provide hands-on activities
- Encourage student reflection
From experience in learning design workshops on a professional level and from readings on an academic level, it would the latter five points receive more attention than that of the former two. If these were not deemed as important or primary in the laying of the foundations of the learning design, then why would Johnson and Aragon have given them such high status in the ordering? Is the lack of attention given on a conscious level that addressing individual differences and motivating students too complex for addressing on a large online scale? Or is the former two points considered too soft or qualitative in nature to understand as to how best to address such needs.
In ‘understanding their learning styles, students can effectively choose the tools that will add the most value to the learning experience’ (Zacharis 2011). However, research by Elen and Lowyck (1998, 1999) has demonstrated that students do not always experience the learning environment in the way intended by its designers. Their perceptions being more focused on its use in how much they will learn in relation to the effectiveness the environment (Entwistle, 1991), this perception has been termed as ‘instructional metacognitive knowledge’ (Elen & Lowyck, 1999) whereby the learner is influenced by conceptions regarding tasks, environments, and learning, any differences between that perceived by the designer and that of the learner can cause suboptimal use of a learning environment (Elen & Lowyck, 1999) as it is the student’s perceptions of the characteristics of the learning environment that will impact on their approach to learning and ultimately their learning outcomes (Entwistle & Tait 1990). Their conceptions of said learning environment are derived from their interaction with it in conjunction with its learning related characteristics (Luytenm Lowyck & Tuerinckx, 2001; Wierstra & Beerends 1996). As noted by Elen and Lowyck (1999), students have conceptions about ‘the way in which instructional features may help or hinder them to learn or to realise (instructional or learning) tasks’.
Building on Saljo (1979), Marton, DAll’Alba and Beaty (1993) have outlines six conceptions of learning:
- Increasing one’s knowledge
- Memorising and reproducing
- Seeing something in a different way
- Changing as a person
It can be possible to have one or all of these conceptions, however literature by Beaty, Gibbs, and Morgan (1997) suggest that there are four different motivational orientations:
Further classification can occur in the application of intrinsic and extrinsic interests (Beaty et al, 1997). For example a student could have a personal motivation, but be extrinsically focused thus also requiring social motivation to achieve their learning outcomes. What can make it difficult for both the designer and the learner if taking into account Johnson and Aragon’s (2003) requirement to address individual differences to motivate the student, is that the possible combinations of individual differences have increased through the application of multiple motivation orientations, which once more reinforces the experiences in which the designer concentrates on the latter five points by Johnson and Aragon, and the learner is left in a confused state.
‘Small differences between students’ learning strategies and teaching strategies in a learning environment may represent a challenge for students to increase their learning and thinking skills’
(Vermunt & Verloop, 1999)
But what if the learner feels that the challenge is to great for them, or is not aware of the very presence of the challenge? As discussed previously such an imbalance between challenge and skill can negatively impact on a learner’s ‘flow’ Csikszentmihalyi’s (1975) with Entwistle and Tait (1990) stating that a student’s perception of a learning environment does have an impact on learning and the quality of the resulting learning outcomes. When faced with such challenges a learner could quickly become objective in their learning, taking from it what only is required as the remainder feels too daunting and confusing for them, this may lead to a greater understanding as to why learners rely on search engines to find the elements of the learning that they require and the pick ‘n’ mix nature to how they consume their online learning.
What is clear from the reviewing of available literature in the light of the learner, rather than the designer’s, viewpoint is that further research is required into the development of understanding into the position that the learner feels they are in, in relation to the material, their learning styles, and conceptions towards achieving their learning outcomes.
Aragon, S.R., Johnson, S.D., & Shaik, N. (2002). The influence of learning style preferences on student success in online versus face-to-face environments. American Journal of Distance Education, 16, 4, 227-244.
Beaty, L., Gibbs, G., & Morgan, A. (1997). Learning orientations and study contracts. In F. Marton, D. Hounsell, & N. Entwistle (Eds.), The experience of learning: Implications for teaching and studying in higher education (2nded., pp.72-86). Edinburgh: Scottish Academic Press.
Bonk, C.J., Wisher, R.A., & Lee, J. (2003). Moderating learner-centered e-learning: problems and solutions, benefits and implications. In T.S. Roberts (Ed.), Online collaborative learning: theory and practice (pp. 54-85). Hershey, PA: Idea Group Publishing.
Boyd, D. (2004). The characteristics of successful online students. New Horizons in Adult Education, 18, 2, 31-39
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco, CA: Josey-Bass
Elen, J., & Lowyck, J. (1998). Students’ views on the efficiency of instruction: An exploratory survey of the instructional metacognitive knowledge of university freshmen. Higer Education, 36, 231-252.
Elen, J., & Lowyck, J. (1999). Metacognitive instructional knowledge: Cognitive mediation and instructional design. Journal of Structural Learning and Intelligent Systems, 13(3-4), 145-169.
Entwistle, N.J. (1991). Approaches to learning and perceptions of the learning environment. Higher Education, 22(2), 201-204.
Entwistle, N., & Tait, H. (1990). Approaches to learning, evaluations of teaching, and preferences for contrasting academic environments. Higher Educations, 19, 169-194.
Felder, R.M., & Silverman, L.K. (1988) Learning and teaching styles in engineering education. Engineering Education, 78, 674-681.
Johnson, S.D., & Aragon, S.R. (2003). An instructional strategy framework for online learning environments. New Directions for Adult and Continuing Education, 100, 31-43.
Kolb, D.A. (1984). Experiential learning: experience as the source of learning and development. Upper Saddle River, NJ: Prentice Hall.
Luyten, L., Lowyck, J., & Tuerlinckx, F. (2001). Task perception as a mediating variable: A contribution to the validation of instructional knowledge. British Journal of Educational Psychology, 71, 203-223.
Manochehr, N. (2006). The influence of learning styles on learners in e-Learning style environments: an empirical study. Computers in Higher Education Economics Review, 18, 10-14.
Marton, F., Dall’Alba, G., & Beaty, E. (1993). Conceptions of learning. International Journal of Educational Research, 19, 277-300.
Meyer, K. (2003). The Web’s impact on student learning. T.H.E. Journal, 30, 5, 14-24.
Saljo, R. (1979). Learning in the learner’s perspective I. Some common-sense conceptions. Reports from the Department of Education, University of Goteborg, No. 76.
Summers , J.J., Waigandt, A. & Whittaker, T.A. (2005). A comparison of student achievement and satisfaction in an online versus a traditional face-to-face statistics class. Innovative Higher Education, 29, 3, 233-250.
Terrell, S. (2002). Learning style as a predictor of success in a limited residency doctoral program. The Internet in Higher Education. 5, 4, 345-352.
Vermunt, J.D., & Verloop, N. (1999). Congruence and friction between learning and teaching. Learning and Instruction, 9, 257-280.
Wierstra, R.F.A., & Beerends, E.P.M. (1996). Leeromgevingspercepties en leerstrategieen van eerstejaars studenten sociale wetenschappen [Perceptions of the learning environment and learning strategies of social sciences students in their first year]. Tijdschrift voor Onderwijsresearch, 21(4), 306-322.
Zacharis, N.Z. (2011). The effect of learning style on preference for web-based courses and learning outcomes. British Journal of Educational Technology, 42, 5, 790-800.