Teatro Aplicado en Comunidad

One important understanding from both Chapter 4 and 5 was that to successfully enhance adaptive e-learning systems, we should consider the personality trait (or type) of each individual learner.

Yet, to understand how and what to be included in designing the adaptive e- learning system is not so straightforward. As a first attempt in this line of study, we considered the personality traits as structuring the learning material.

The assumption of this study is that learners’ cognitive style (which comes from personal trait) significantly influences their preferences for a particular learning material structure (Blaylock & Rees, 1984; Hough & Ogilvie, 2005; Moallem, 2003). For

instance, Experiment 3 showed that ISFP (Introvert, Sensing, Feeling, Perceiving) learners performed poorly as they were being taught by ELM-ART, arguably because they tend to seek freedom to learn at their own pace (Keirsey, 1998; Myers &

McCaulley, 1985), while those who are ENTJ (Extravert, Intuitive, Thinking, Judging) type learners performed well with the adaptive system because they appreciate planning and prefer sequential learning, which means they fitted well with ELM-ART. Therefore, the designers of an adaptive e-learning system may need to consider this aspect in order to make an effective learning system design for diverse learner groups. This is what we are seeking in this chapter, to see how to incorporate the personality trait in designing the structure of learning materials.

Previous studies (e.g., Riding & Fanning, 1998; Riding & Rayner, 1999; Zang, 2002; 2006) suggested that different personality types cause preferences for different learning material structure. This is probably because different personality traits would generate different cognitive styles to process the information given (Blaylock & Rees, 1984). For example, the extraverted learner tends to benefit from general ideas, then moving toward more detail. This style helps them pay attention to the whole learning experience first (Soles & Moller, 2001). In contrast, the introverted seem to be more self-reliant, and they may benefit more from the conceptual information that emphasises fundamental understanding first to generate a big picture of their learning process

(Myers, 1993; Myers et al., 1998). Therefore, perhaps, different learners would have different preferences for the structure or flow of the contents delivered.

In e-learning material design, there have been two major strategies: Breadth-first and depth-first (Ford & Chen, 2001). The breadth-first strategy concentrates on

establishing on an overview of learning outcomes before moving to further details. Hypothetically, it may be well suited to the extraverted learner due to its overall picture given prior to every detail of the course. By comparison, the depth-first strategy

employs a bottom-up approach, starting from low-level details first (basic principles) and then moving toward more global perspectives, which may meet the preference of the introverted. For example, consider the course material of HTML (HyperText Markup Language), simply consisting of three lessons, i.e., the concept of HTML (lesson 1), working with HTML (lesson 2), and publishing HTML (lesson 3). Lesson 1 would generally have several sub-sections such as definition, background, structure of HTML, which introduces the basics of HTML. The “Working with HTML” lesson would then provide information on practical coding in HTML, such as webpage

formatting, and style tags for designing web pages in its subsection. Finally, it follows a lesson on how to upload and maintain web pages for publishing. If the course structure is designed in the breadth-first strategy, it firstly presents all the top levels, and then describes the detailed subsections. This structure is very likely to help the learners capture what they should learn firstly, in the sense that they can hold the overall course structure in advance so they can find what contents would be more important than the others. In contrast, the depth-first strategy takes a different way to deliver the same contents. It explains all the details under each lesson. That is, it firstly introduces the definition, background, and structure of HTML under lesson 1 and then moves to lesson 2 for the full exploration and finally delivers lesson 3 in full details. That means the learner does not have any opportunity to capture what is to be followed, so that it is very

unlikely that the learner can organise all the learning contents before they learnt all the relevant lessons, but they are certain to haveacknowledged every detail before

obtaining the global outline of the course. This approach is believed to be particularly useful for learners who are more inductive (Trochim, 2006); we suggested that it would be introverted learners.

Several studies (e.g., Felder & Brent, 2005; Ford & Chen, 2001; 2000b; Hayes, 1996) concluded that these two strategies (depth-first and breadth-first) would be subject to learners’ personality styles if given the opportunity to use their preferred methods of learning. That is, introverted learners who are usually inductive learners are likely to have benefits from the depth-first strategy, the extraverted from the breadth- first strategy.

Yet, a number of other studies identified that the personality type itself has nothing to do with preference for learning material structure (e.g., Stash & De Bra, 2004). Felder et al. (2002) showed that the learners who have learning materials

mismatching their personality type may perform better in their learning session, because in the long term, it can encourage them to develop their own learning strategies that cope with wider range of materials and experiences in the future. That is to say, extraverted learners are aware of the need to develop the organised skills that

introverted learners generally have, while introverted learners can have opportunities to enhance the multidisciplinary combination of skills that the extraverted learners

generally have (e.g., Entwistle, 1990; Honey & Mumford, 1992), by using learning material structures that mismatch their personality type. Hence, this chapter explores this issue empirically with an adaptive e-learning system, an example of using personality traits in designing effective adaptive e-learning systems.