Learning about Design Part 3

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.’

(Zacharis, 2011)

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:

  1. Address individual differences
  2. Motivate the student
  3. Avoid information overload
  4. Create a real-life context
  5. Encourage social interaction
  6. Provide hands-on activities
  7. 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
  • Applying
  • Understanding
  • 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:

  • Personal
  • Vocational
  • Academic
  • Social

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.

Learning about Design Part 2

This blog post comes a little later than planned due to being a little bit under the weather of late. However now feeling increasingly better than previously, so time to crack on with the studies once more. Whilst away from my laptop I captalised on old-fashioned hard copy papers and highlighter pens, so over the next few days (completely aware Christmas Eve is in a few short hours!) I will be writing a number of posts from my readings on the theories and concepts of learning design and how this may impact on learner motivation.

Once again, the papers I have sourced relate to formal accredited for-fee study, though I will be drawing parallels wherever I can to informal non-accredited for-free learning and applying where possible.


Learning Design has been a fairly recent noted emergence on the educational landscape, however Holden (2009) commented that design education at The Open University (OU) has been provided since the 1970’s due to it’s unique nature of delivery of distance education to scale. Due to this scale Holden noted that the OU’s approach needed to be more generalist than specialist in view of designs used. This more generalist view is understandable given the sheer volume of students that the OU delivers education to, as Koskinen et al (2011) describes as “the ‘halfway’ between people and things”. Considering the number of people and the range of courses on offer it could be difficult to create a more specialist approach.

However, as record, theorised, and reflected upon by numerous academics since the creation of the OU, that there can be “resistance to learning” (Atherton 1999) when the ideas being presented are incompatible with a student’s view of education and/or its design. In the situation of informal learning, which is on a much larger scale to formal learning (the OU has circa 250,000 formal students, and circa 10 million informal learners), the frequency of resistance could be deemed to be higher of that considered within formal learning, which in turn could lead to impacting on learner motivation.

Bloom’s taxonomy (1984) is still considered to be the foundations of educational design, however it is important to note that it has received academic criticism for being essentially behaviourist in its principles and hierarchical in its construction. Anderson and Krathwol (2001) addressed a number of this criticisms in their updating of Bloom’s taxonomy by the introduction of a number of elements to the construction of the taxonomy such as addition of ‘actions’ (Remembering and Understanding) to the primary feature of ‘things’ (Knowledge and Comprehension).

As summarised by Conole et al (2004) when referring to learning design toolkits there is a range of learning theories in addition to behaviourism, which include:

  • Cognitive
  • Constructivist
  • Activity-based
  • Socially situated learning
  • Experiential
  • Systems theory

Though there is a range of theories to draw upon in the creation of learning design, Conole et al (2004) note:

‘Many described instances of e-learning claim to draw upon theoretical positions, such as constructivism, without explaining how they embody the principles and values of that approach (Oliver 2004). Perhaps as a result many designs reflect ‘commonsense’ rather than theoretically informed design’

In the creation of learning design toolkits Conole et al (2004) wish to address this re-occurrence of the reliance of common sense to develop learning material through the development of practical plans for action (Conole & Oliver 2002), and differentiation of approaches to evaluation (Conole, Crewe, Oliver, & Harvey 2001). Through the application of a toolkit it may even be possible to engage the process of reflection-in-action (Schon 1987), or Sadler’s (1989) approach to the monitoring of the quality of own work as part of a summative learning process. Walker (2009) states that in addition to synchronous reflection reinforced by asynchronous summative reflection should be a mechanism to feedback and the student’s understanding of feedback as a response, thus creating a student-centred approach (Biggs and Tang 2011) to increase the effectiveness of the learning.

However, once more it is important to consider that the above is related to formal study at a lower scale and narrower range (or of less frequency) than that of informal learning. The introduction of the element of informal learning creates an extra tension that makes it difficult to;

‘achieve balance between process and product, between responsive and contractual accountability and between individual and system outcomes’

(Gleeson & Donnabhain 2009)

The introduction of informal learning to a wider, larger, and subsequently diverse population is that there is possibly the over reliance of the system to deliver the learning, resulting in more of a generic response as part of the contractual obligation of the learning material. This over reliance can lead to the sense of ‘indoctrination’ (Chomsky 2012) in the trapping of learners into a system by conducting education of a market and its learners as customers. The difference here, in comparison to formal students, is that informal learners are more consumerist in nature than that of a customer. There is no monetary exchange required so the marketplace is more open and the learner can abandon their ‘acquisition’ at any time. In informal learning there are no barriers to exit, so motivation is one of the primary bargain chips in this marketplace. If a learner does not feel like a VIP in their exchange of time and motivation for informal learning, or that the requested learning outcomes are deemed too ‘pricey’ then the learner is able to either increase their time and motivation to create ‘value for money’ or decide that the expense is to great in consideration of their proposed investment.

It is important therefore to consider all the stages of learning design to ensure that the design created is ‘fit for purpose’ and the marketplace. Conole et al (2004) state that there a five stages for consideration:

  1. Reviewing learning theories
  2. Identifying common characteristics across the learning theories
  3. Building a model in relation to the theories
  4. Mapping learning theories to the model, thus identifying learning clusters
  5. Applying and testing the model, developing the learning design toolkit in relation to learning activities and associated mediating tools and resources.

Conole et al (2004) then develop the toolkit further as a model to include the following elements:

  • Individual – where the individual is the focus of learning
  • Social – learning developed through interaction with others (discourse and collaboration)
  • Reflection – experiences transformed into learning through conscious reflection
  • Non-reflection – the explanation of learning through conditioning, process learning, skills learning, and memorisation (Jarvis, Holford, & Griffin, 1998)
  • Information – through text, artefacts, and bodies of knowledge form learning and experiential foundations
  • Experience – through direct experience, activity, and practical application

Conole et al (2004) as part of their writing develop a number of representations of the six elements creating connections and relationships between the elements dependent upon the mapping of the learning theories to the aforementioned learning models. However, it is important to consider that all of the six elements, regardless of the models to which they are mapped to, seem to be of equal weighting. Though beneficial to have the presence of all six elements within a learning design, should not the extend of their presence also be considered? Whereby creating learning designs for informal learning to be delivered at mass, perpetually, and online to an ever moving community of informal learners, should consideration be given to the greater presence of certain elements over others? Would this cause a lever effect on the levels of learner motivation?

Dimitriadis, McAndrew, Conole, and Makriyannis (2009) argue that teachers don’t fully understand OER (Open Educational Resources) enough to effectively reuse them, coupled with the need then for them to apply effective learning design suitable for the plethora of learners increases the difficulty in the creation of suitable learning for context. Teachers may understand that learning can be developed through the ‘mediation of artefacts’ (Kuutti, 1991) to include ‘instruments, signs, language, and machines’ (Nardi, 1995), but Dimitriadis et al (2009) state that this context should also include ‘a process of abstraction of learning activities, and may include models, patterns, case studies, vocabularies or iconic representations’ as defined by Conole (2008). These are all different elements that comprise of the ingredients to create OER objects for learning. These objects may be large and complex enough to be considered as individual learning designs, or most commonly are building blocks to the creation of a learning design. In the case of MOOCs (Massive Open Online Courses) it is prevalent, given the length of the courses, that they are constructed from individual OER with an adjoining or flowing narrative to create the learning journey. What is important to consider here is that each of these elements may have been designed differently, but different academics, for different purposes, potentially causing an ebb and flow effect to the learning that could have an impact on learner motivation to complete all of the various stages. It this sequencing of methods and media (Lewis & Merton 1996) that requires close scrutiny in the construction of a learning design and the establishment of its course overview (Harrison 1994), such ‘orchestration’ (Littleton, Scanlon, & Sharples, 2012) in the planning, management, and guidance of learning design needs close attention, not just for the narrative of the course, but also the elements within it.


Anderson, L. W., & Krathwohl, D.R. (Eds). (2001). A taxonomy for learning, teaching and assessing: A revision of Bloom’s taxonomy of educational objectives. New York: Longman.

Atherton, J. (1999). Resistance to learning: a discussion based on particpants in in-service professional training programmes. Journal of Vocational Education &Training, 51(1), 77-90. doi: 10.1080/13636829900200070

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university: What the student does. (4th ed.). (Society for Research Into Higher Education). Maidenhead: Open University Press.

Chomsky, N. (2012). The purpose of education. Retrieved from http://www.learningwithoutfrontiers.com/2012/02/noam-chomsky-the-purpose-of-education

Conole, G. (2008). Capturing practice: the role of mediating artefacts in learning design. In Handbook of Research on Learning Design and Learning Objects: Issues, Applications and Technologies,  L. Lockyer, S. Bennett, S. Agostinho, and Harper, B. (Eds), 187-207, Hersey PA: IGI Global.

Conole, G., Crewe, E., Oliver, M., & Harvey, J. (2001). A toolkit for supporting evaluation. The Association for Learning Technology Journal, 9(1), 38-49

Conole, G., & Oliver, M. (2002). Embedding theory into learning technology practice with toolkits. Journal of Interactive Educational Media, 8. Available: http://www.jime-open.ac.uk/ .

Dimitriadis, Y., McAndrew, P., Conole, G., & Makriyannis, E. (2009). New design approaches to repurposing open educational resources for collaborative learning using mediating artefacts. In: ascilite 2009: Same places, different spaces, 6-9 December 2009, Auckland, New Zealand.

Gleeson, J., & Donnabhain, D.O. (2009). Strategic planning and accountability in Irish education. Irish Educational Studies, 28(1), 27-46. doi:10.1080/03323310802597291

Harrison, C. (1994), ‘The role of learning technology in planning change in curriculum delivery and design’, ALT-J, 2(1), 30-7

Holden, G. (2009). Design at a distance. Paper presented at the Engineering and Product Design Education Conference. Brighton.

Jarvis, P., Holford, J., & Grifin, C. (1998). The theory and practice of learning.  London: Kogan Page.

Koskinen, I., Zimmerman, J., Binder, T., Redstrom, J., & Wensveen, S., (2011). Design research through practice: From the lab, field, and showroom. Amsterdam: Elsevier, Retrieved from http://bscw.wineme.fb5.uni0siegen.de/pub/bscw.cgi/d814752/DesignResearchComplete.pdf

Kuutti, K. (1991). Activity theory and its application to information systems development and research. In Information systems research,  H.E. Nissen (Ed.), 529-549, Amsterdam: Elsevier Science.

Kuutti, K. (1997). Activity theory as a potential framwork for human-computer interaction research. In B. Nardi (Ed.),  Context and consciousness: activity theory and human-computer interaction (pp. 17-44). Cambridge, MA: MIT Press.

Lewis, R. & Meron, B. (1996). Technology for Learning: Where are We Going?. Independent Learning Unit position paper, University of Lincoln and Humberside.

Littleton, K., Scanlon, E., & Sharples, M. (2012). Editorial introduction: Orchestrating inquiry learning. In K. Littleton, E. Scanln, & M. Sharples (Eds.), Orchestrating inquiry learning.  New York: Routledge.

Nardi, B. (1995). Studying context: A comparison of activity theory, situated action models and distributed cognition. In Context and consciousness: Activity theory and human-computer interaction, B. Nardi (Ed.), 690101. Cambridge, MA: MIT Press.

Oliver, R. (2002). Winning the toss and electing to bat: Maximising the opportunities of online learning. In C. Rust (Ed.), Proceedings of the 9th improving student learning conference (pp. 35-44). Oxford: OCSLD.

Sadler, D.R. (1989). Formative assessment and the design of instructional systems. Instructional Science18(2), 119-144. doi: 10.1007/BF00117714

Schon, D.A. (1987). Educating the reflective practitioner. San Francisco, CA: John Wiley and Sons.

Walker, M. (2009). An investigation into written comments on assignments: do students find them usable? Assessment & Evaluation in Higher Education, 34(1), 67-78. doi: 10.1080/02602930801895752