9.3: Design to Enable Human Capabilities

For the past 50 years, two main trends have been observed in general education:

1. the socio-cultural focus; and
2. the integration of technology in educational practice.

However, still in its infancy, e-learning has yet to construct models of design to reach socio-cultural learning targets. There is as yet to employ consideration of the learner and user (Wallace, 1999; Smulders, 2002). Poor interfaces do not support e-learners efficiently and effectively, even though the existing commercial and open source learning management systems (LMS) provide several applications and tools. Most learning management systems are based on a constructivist model, and not on an e-learning community and reflective model of supporting distance education (Rumble, 2001). There are, therefore, no multiple perspectives of e-learning’s theoretical framework. Evaluators are still not supported by coherent, interdisciplinary evaluation frameworks and tools. This results in inadequate understanding and lack of descriptions of quality factors. To Silius and Tervakari (2003), one evaluator, whether s/he is a teacher or a systems’ designer or a quality planner, can hardly be an expert in all aspects. Collaboration between the stakeholders is the first step towards the adoption of a more social model for e-learning.

The Social Dimension of Learning in Design

Computer-supported collaborative learning (CSCL): The social aspects of learning with the aid of computer networks first appeared in CSCL. This followed the computer-supported collaborative work (CSCW) that utilised ethnography (Garfinkel, 1967) in systems design. Ethnography provides descriptions of qualitative and quantitative data about human social phenomena based on fieldwork, and was used to search for descriptions that could provide abstract specifications for systems design, i.e., finding ways to communicate to the designers what users want. Thus, the research of Hughes and colleagues was based on socio-technical design (STD) (Mumford, 1983; Fan, 2006) to inform the designers of system requirements. The STD mission was to assist system designers to maximize human gains while achieving business and technical excellence (Mumford, 1983). It recognises the interaction of technology and people, and produces work systems that are both technically efficient and have social characteristics. CSCL is linked to STD via CSCW (Hughes et al., 1997) and is anchored in the notion that, the system cannot be accurately understood as each property depends on the other.

Computer-supported collaborative learning (CSCL) was based on theories that emphasized the social dimension of learning, such as distributed cognition (Hutchins, 1995; Salomon, 1993); activity theory (Engestrom, 1987; Kuutti, 1996); situated learning (Resnick, Levine & Teasley, 1991); Greeno, Smith & Moore, 1993); collaborative learning (Crook, 1994); and legitimate peripheral participation in communities of practice (Lave & Wenger, 1991; Wenger, 1998; Wenger et al., 2002). Collaborative computer-supported collaborative learning has contributed significantly to the socio-cultural field.

Network-supported collaborative learning (NSCL): NSCL has emerged as a similar educational paradigm. It includes cognitive sciences, sociology, and computer engineering. See Banks, Goodyear, Hodgson & McConnell, 2004; Steeples and Jones, 2002. This interdisciplinary approach has also introduced the role of learning technologist (Conole & Oliver, 2002; Conole, 2004). However, owing to inherent difficulties in performing evaluation in general, as well as evaluation in its own field, very few systematic and complete studies have been reported in NSCL literature (Retalis et al., 2006).

Research in computer-supported collaborative learning and network-supported collaborative learning have found common ground between disciplines, and is now focused on learners working collaboratively. There is still the need, however, for the teacher and the technologist to acknowledge the individual e-learner’s requirements. In fact, the learner behaves as a learner, a user, and a customer. Even though learning technologists have aimed to fill this gap, the result is still techno-centric design and poor usability (Diaz, 2002; Notess, 2001). The problem remains. There is need for learning management systems to provide an integrated platform for collaborative learning in communities of practice (CoP, Lave & Wenger, 1991). Delivery of the learning product, supporting management, engagement, and tracking of information and activities should facilitate e-learning communities. The Web 2.0 philosophy and tools are currently in favour of such initiatives, but the systems are still in the first stage of development supporting information provision that community knowledge building.

Socio-technical design requires social software qualities of sympathy, trust, and integrity (Mumford, 1983). In e-learning this has been referred to as affective learning (AL). Affective learning properties link the individual with the community. Such properties include the emotions, intentions, attitudes, interests, attention, awareness, trust, motivation. or empathy enable communication, consultation, and participation (Zaharias, 2004). For example, Grosz and Sidner (1986) suggest that the discourse structure is intimately connected to intention; for instance intentional information in discourse structure creates adaptation of a conversational channel (Woodruff & Aoki, 2004). Empathy is another example, which is considered essential for participation in online communities (Preece, 1999; Preece & Ghozati, 2000; Lambropoulos, 2005).

Affective learning in design: A learner-centred approach to e-learning quality relies not only on cognitive but also on emotional and affective learners’ engagement (Zaharias, 2004). Such a learner-centred approach acknowledges the importance of context, and views learning as a social and collaborative process. In the learner-centred paradigm, learners are the focal point— the centre of the learning process. They should take responsibility for their own learning, reflect, and make sense of their experiences. Interconnections between the dual persona of the learner as a user, as well as the inclusion of affective learning factors are the links between the individual and the learning community in the e-learning world. The development of brain research (LeDoux, 1998) and cognitive neuroscience allowed Rizzolati and Arbib (1998) to discover the areas where the mirror neurons are located, interacting in both hemispheres (Broca are 44 and PE/PC). Such neurons are responsible for representing the existence of other people in the brain. This discovery resulted in the scientific identification of empathy, widespread in online communities (Preece & Ghozati, 2000).

According to Zaharias (2004), such affective networks justify the why in learning as humans pursue goals, develop preferences, build confidence, persist in the face of difficulty, establish priorities, and care about learning. And yet, affective networks are not considered important in educational technology. It is generally difficult to engineer empathy, but with the advantage the affective learning factors provide, learning theories for the individual can co-exist with socio-cultural learning. The learning activity is the outcome, as Zaharias stressed. Learner-centred frameworks and principles should require learners to be active participants in every quality assessment process. In order to achieve this, Zaharias provided a set of quality principles and their implications for e-learning instructional design quality. His seven quality principles associated with specific implications for e-learning design quality are:

• individual differences relevant to learning styles and preferences
• information overload
• contextual learning
• social learning
• active learning
• reflective learning
• emotional engagement focusing on motivation.

Zaharias’ quality principles echo the need for a systems’ design model that can support the formation of e-learning communities for the benefit of the individual and the community. Currently, there is still need of support of collaborative activities and active participation integrated applications. The first generation of learning management systems (LMS) was focused on information provision and management rather than learning. The new generation of LMSs following Web 2.0 philosophy needs to support the learners in their collaborative activities.

Enabling Human Capabilities: Design for Learners as Users and Users as Learners

Design for learners-users-customers refers to Shackel’s definition of user-centred design (1991). He suggested that designers need to enable human capabilities. To achieve this, the individual needs to meet the purpose of systems design without any additional cognitive and physical struggle to use it. The International Organization for Standardization (ISO) defined usability as a measure of quality of user experience when interacting with a system, in terms of effectiveness, efficiency, and satisfaction (ISO FDIS 9241-11, 1997). Faulkner (2000) suggested that users who do not have to learn to use the system, as the system is already easily used, are freed from the restrictions of their own ability to learn. Initial adaptation of the right attitude is of primary importance (Faulkner, 2000, p. 78). This implies that ensuring usability enables the ability to learn.

Instructional design (ID) is a process of resolving instructional problems through systematic analysis of learning conditions. ID starts with the initialization and project planning phase (how the instructional design is carried out); the design and development phase (appropriate strategies and approaches in targeted contexts); a QA phase is focused on evaluation and deployment. The general observation of Bichelmeyer and colleagues (2004) is that the process for most instructional designers is the same: analyze, design, develop, implement, and evaluate (ADDIE). However, Schwier and colleagues (2006) complain that systematic models of ID do not reflect actual practice, are cumbersome, ineffective, inefficient, and costly to implement. This is due to several reasons including unfamiliarity of stakeholders with ID, division between ‘academic’ and ‘corporate’ approaches, and unawareness for the need of quality standards. He has reason. Whereas learner-centred design (LCD) is focused on making users more effective e-learners, user-centred design (UCD) is focused on making e-learners effective users in order to free them from cognitive and physical constraints, making the system easy to use. These two activities as Wallace (1999) claimed should be networked on shared social interfaces for users-as-learners and learners-as-users. This is e-learner-centred design.

To date, the focus has been on the technological (techno-centric interfaces) and not on the social aspects of learning. Thus, there are still issues for useful and usable design in support of e-learning (CHI SIG, 2001). Researchers are still seeking a design to solve such quality problems (Muir et al., 2003; Silius et al., 2003b; Zaharias, 2005). A socio-technical approach for a learner-centred design (LCD) was adopted in turn by Soloway et al., 1994; by Norman & Spohrer, 1996 and Wallace et al., 1998. Their work aimed to bridge the gap between learners as users. At the time, Norman and Spohrer suggested that LCD has three dimensions:

• engagement
• effectiveness by measuring the quality
• viability of interventions.

In support of the third dimension, they observed that projects “won’t scale to real curriculum needs or large numbers of students, or diverse content areas, or to everyday teachers and students rather than handpicked ones”. They also emphasized the importance of active participation, evaluation, and implementation of design interventions in real-life settings.

Their example of a combined LCD framework has been developed by later researchers along different lines. Whereas Muir and colleagues (2003) worked on pedagogical usability for online courses for learning language, Daniel and colleagues (2005) worked on a variety of user-centred evaluation approaches to consider methods for determining whether a learning community exists, attempting to isolate and understand interactions among its constituent elements. Zaharias (2004) on the other hand developed a questionnaire-based usability evaluation technique that relies upon web usability and instructional design parameters, associating them with a motivation to learn. The latter is proposed as a new affective-oriented measure for e-learning usability.

It appears that combined frameworks are necessary to go out of the control room and controlled experimentation and adjust the interventions to stakeholders’ needs. In addition, measurement and evaluation is not towards control but to support successful designs and eliminate existing problems.

Every learning context is unique. Parker (2003) believes that there is an ideological congruence with the reduction of “citizens” to “taxpayers”, and as the focus moves to “value-added” activities, the terrain of the debate is being narrowed to shorter and shorter transactional terms. Their focus on institutional policy and teaching with learning styles based on all stakeholders’ targets is not a disadvantage and, in this chapter, it is worth considering a focus depending on active participation in collaborative learning. Understanding the controlling processes and improving them by evaluation and assessment will eliminate existing problems.