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Abstract

The use of technology to support learning is well recognised. One generation ago a major strand of human–computer interaction research focussed on the development of forms of instruction in how to interact with computers. Today, however, the advanced usability of modern technologies has all but removed the presence of many user manuals. Learners, educators and developers now need to know not how to use the technology per se: the adoption of user-centred design has solved much of this. Rather, they must understand the nature of learner behaviour across contexts: insight is required into ‘how to learn’ using mobile technology and ‘how to manage and structure’ learning behaviour across changing contexts whilst mobile. To this end, we advocate a reinvention of effective user instruction at the metacognitive level, and use a classic framework developed in the early 1980s to structure our conceptualisation of the onward research and development effort that is required for 21st century user instruction and support.

Keywords

Context awareness learner characteristics learning contexts instruction metacognition mobile learning psychology

Introduction

The Second World War served as a major impetus to develop instruction in ‘how to use’ technologies and tools. This instruction generally came in the form of user manuals. Bell’s instruction booklet for the telephone provided advice on how to use this relatively novel technology, including guidance on: the different types of telephone that existed, how to negotiate the buttons and dials (Bell Telephone System, 1951). Crucially, it recognised the need to be mindful of the contextual circumstances/situation of the potential recipient of the call.

In the early 1980s the adoption of personal computers (PCs) brought with it the very significant challenge of ‘how to use’ them. This challenge was met with varying degrees of success by a new wave of user instruction that drew upon learning theory and psychological insights into human behaviour and included innovations such as task-oriented minimalism (Carroll, 1990), guided exploration cards that encouraged user-driven exploration (Carroll, 1990) and ‘training wheel’ interfaces which hid functions that might lead to errors. The success of these new psychologically-informed ways of supporting users was demonstrated repeatedly (Carroll and Carrithers, 1984; Ramsay and Oatley, 1992).

Minimalist principles recognise that users want to use the tool to carry out a task and that they need assistance to recover from errors. Minimalist documentation supports quicker, superior learning and greater self-reliance (less reliance upon the documentation) (Lazonder and van der Meij, 1993; van der Meij and Lazonder, 1993). The comparative effectiveness of task-focused minimal manuals over system-centric manuals was demonstrated in a meta-analysis by Ginns et al., (2006). This indicates that psychologically informed minimalist instruction has been highly successful and offers strong foundations on which to build e-learning instruction.

A Heideggerian perspective on ‘how to’ and ‘in order to’

In many cases, ‘in order to’ use a computer, prior knowledge, in the form of user instruction is required. The notion of ‘in order to’ has its roots in the philosophical work of Martin Heidegger. Heidegger (1962) took the view that individuals perceive and understand the words as a ‘whole’ by making sense of the relationships between the entities in the world. He used the example of a workman’s tools: one is unaware of them when they work and one can focus on the task in hand.

When the tool is broken, one focuses on the tool and not the task. Crucially, it is not necessary for a tool to be broken for one to become aware of it: it is merely sufficient that it functions sub-optimally. Similarly, if any poorly designed modern day technology is difficult to use, the user – or learner – must allocate mental time and effort to understanding ‘how to use’ the tool rather than ‘how to do’ the task.

The psychological perspective on learning how to use

The discipline of psychology played a central role in characterising and predicting human interactions with computers. Psychological theory and method provided the necessary insights into human behaviour that drove the user-centred design revolution. The aim was to identify and embed appropriate principles of psychology within the design of technology to enhance usability and thus reduce the person-system divide (Norman, 1986).

From the 1980s through to the present day, approaches to learning have evolved from more traditional, passive didactic ones, where the emphasis is on transmission of information, to those that recognise the socially contextualised and socially constructed nature of learning. This reflects Vygotsky’s (1978) observation that learning is socio-cultural in nature, and that it emerges from one’s interactions with others. Nowadays, this is reflected in the current trend of collaborative e–learning via blogs, wikis and online discussion boards. During this time period, significant advances were also made in understanding the nature of learning from the perspective of the learner such as the importance of specific learning events and the recognition of motor and verbal learning categories (Gagné, 1985; Gagné and Briggs, 1979; Gagné and Driscoll, 1988).

Key principles that underlie constructivist learning, such as the significance of person–environment interaction and engagement with others, prompted the development of learning design (Cunningham et al., 1993; Savery and Duffy, 1995). For example, Sweller and Chandler (1994) advanced their cognitive load theory which made the case for a careful examination of the intrinsic (that which cannot be controlled) and extraneous (that which can be manipulated by the manner in which information is presented) cognitive load imposed by learning material. Reconfiguring the source of responsibility so that it now lies with the computer designer/educational provider had significant long term consequences for both system design and user instruction: the burden of cognitive responsibility was shifted from the user to the computer/system.

Recently there has been a shift from the concept of Science 1.0, which was reductionist in nature, to Science 2.0 which considers real world sociotechnical systems (Shneiderman, 2008). This is a useful way of characterising the evolution of the domain of human–computer interaction. In its inception, the domain was exemplified by task–action grammars to capture the correspondence between tasks and actions (Payne and Green, 1986, 1989), reductionist methods such as cognitive walkthroughs (Lewis et al., 1990; Wharton et al., 1994), cognitive task analysis (Hoffman et al., 1998; Ryder and Redding, 1993) and keystroke level models such as Goals, Operators, Methods and Selection Rules (Card et al., 1983). Such tools and techniques view humans as information processors to be queried about their interactions with computers, with their outputs becoming step-by-step stages in cognitive processes which fill the pages on user manuals of the ‘how to’ style.

Thankfully, this reductionist emphasis was complemented by the ecological perspective of Gibson (1977, 1979), who advocated the concept of affordances: propensities of the world that invite particular forms of interaction. By situating the user in their wider ecological context, user instruction could be viewed as an extension of the wider user interface and formed part of the quest to reduce the gulf between user and computer (Norman, 1986). Recently, however, Oliver (2005) has questioned the continued viability of the concept of affordances in new e-learning contexts as it has drifted from its original use.

Despite its flaws, the heavily reductionist approach to understanding how people interact with computers has proven very successful. The past decades have seen the broadening of computer use out from personal office-based technologies such as the word processor to public technologies such as automatic teller machines. Automatic teller machines are ‘walk-up and use’ public technologies. The general public do not have to read a manual in order to use them. The quest for supremely fluid, usable, effective and pleasurable interactions has to a very great extent been won. Norman’s (1986) gulf of execution and evaluation that separate user and system have been, if not removed, then certainly bridged and narrowed.

Re-contextualising ‘how to’ for the 21st century

It is clear that the reductionist efforts of the 1980s and 1990s were very successful. User manuals and user interfaces afforded interaction as a consequence of embedding an understanding of user psychology. We also recognise that significant progress was made due to consideration of contextual aspects such as Gibson’s (1979) affordances. If we are to meet the challenges and maximise the affordances presented by the mobile dimension of Web 2.0 technology for socialising and learning, then mobile technology use needs to be situated within the appropriate contexts and these contexts will be more variable than traditional static use. For example, social media on mobile devices enables communication irrespective of the context of the interlocutors; that is, whilst the communicating parties are on the move, in changing contexts of use and changing contexts of time.

We define mobile learning as ‘the use of wirelessly connected devices to augment learning and teaching within and between different psychological, social, physical and temporal contexts’ (Terras and Ramsay, 2014: 109). Learners require a new variety of user instruction, a brand that informs them how to use technology to learn. It should not be assumed that because many students are immersed in technology in the social aspects of their lives that they will automatically be skilled at using the same technology to learn (Terras et al., 2011). We have previously highlighted the importance of user skills in addressing the challenges of mobile learning (Terras and Ramsay, 2012), in maximising the potential of open education resources (Terras et al., 2013) and in managing the temporal challenges of mobile learning (Terras and Ramsay, 2014). If competent users of social technology are to become effective e-learners they do not need to be instructed in how to use technology per se but, rather, on how to use technology to learn.

Support for new contexts of learning – a case study

To illustrate the problem of managing user interaction, it is useful to examine a case study of online gaming. In online gaming, user instruction is anchored in the concept of ‘discoverability’ (Norman, 1988) – allowing the user to uncover the functionality by ‘probing’ the system’ (Gee, 2007) in the moment of the action itself. At the time of writing, Vance (2014), an online game instructional designer, commented on the challenge facing game designers, of allowing user discovery on the one hand, the teaching of how to use the game by the designer on the other, and the tension between the two. User support comes in the form of clues, hints and other forms of electronic ‘hand-holding’ in online games. Hand-holding might also include a companion and various form of reminders of how everything works, walkthrough guides, and hints and tips on discussion forums. Whilst hand-holding is reflective of instructional ‘scaffolding’ (Bruner, 1978), the question of its use and application, is debated heatedly by online gamers.

This provision of user-support within games typifies the challenges we now face: the provision of user guidance and support in newly emerging contexts of learning, both formal and informal. Learners, educators and developers now need to know not how to use the technology per se: the adoption of user-centred design has solved much of this. The new challenge is to maximise the potential of mobile learning. If one is to achieve this, it is necessary to understand and therefore support a range of effective learner behaviour across contexts. The issue of instruction in ‘how to use’ has evolved into how to learn using mobile technology and how to manage and structure learning behaviour within and across new contexts of learning.

The evidence that underpins our reconceptualization of ‘how to’

In this section we outline the major psychological challenges that are emerging in the field of user instruction and support. These challenges stem from the changing spatio-temporal dimension of mobile learning, the shift from uni- to multi-dimensional function, the increasing importance of metacognition in the use of digital communication technologies, and the emergence of user-generated content that necessitate the need for a resurgence and re-conceptualisation of user-instruction for the 21st century. We present each of these challenges in turn below.

E-learning contexts: the spatio-temporal dimension

One generation ago, considerable research effort was focussed on formal contexts of use such as the workplace (e.g. Adler and Henderson, 1994; Ishii et al., 1993; Mantei et al., 1991). Learning locations and learning times were determined by organisations and by teachers, now they are (co-) determined by learners. The psychological implications in particular of learning across time and space has been explored by Terras and Ramsay (2014) who outlined the importance of considering both the physical and experiential aspects of time, and how information is sequenced over time as these factors are key to capturing the temporal dimension of mobile learning. Furthermore they highlight the need to recognise that temporal changes are often accompanied by locational change.

These changing spatio-temporal contexts are challenging because memory is context- and state-dependent (Godden and Baddeley, 1975; Woike et al., 2009) and cognition is distributed over time and space (Hutchins, 1995; Suchman, 1987, 2007). Therefore, users require an element of awareness and control over their prospective memory (memory for intended future actions) and good metacognitive skills to allow the planning, control and allocation of the cognitive resources that support learning effectively. Finally, users are different, therefore it is important to consider individual differences in their psycho-social profile as well as preferences and skills (Terras and Ramsay, 2014). Therefore, any ‘how to’ instruction will need to be designed to allow personalisation by the 21st century learner.

In public spaces we share common facilities and different individuals use the space for different purposes at different times. For example, the park is a public amenity that is used by joggers, dog-walkers and sunbathers and others at different times for different purposes. There is signage to guide behaviour in these public spaces – for example, ‘Do not walk on the grass’ (park) and ‘No talking’ (library). Indeed, Goffman’s (1963, 1971) concept of civil inattention helps one to understand how shared social spaces, in particular, densely-populated spaces, are negotiated. Civil inattention is required for the successful co-existence of individuals in such spaces, where one neither aggressively ignores nor actively intrudes upon the existence of others in the shared space. Rather, the space is neutrally inattended.

The importance of this jointly-achieved state of being needs, arguably, to be actively understood by mobile learners habituating shared online spaces. In the Web 2.0 online world, where learners only share virtual space, and do not share the same physical space, the challenge is to increase the online learner’s awareness of the shared and common nature of the virtual space. As in physical space, such self-regulation of behaviour will occur over time. The online world, like the offline one, is a common resource, used by many, for different purposes at different times. What differs is the availability of personal and contextual cues to support effective and appropriate interaction.

The uni-function to multi-function shift: opportunities and challenges

Over the past 25 years there has been a shift in the core function of computing technology. Telephones were originally designed for the sole purpose of supporting interpersonal communication; early PCs were designed for the sole purpose of word/document processing, as discussed in Carr (2011). More recently, these formerly uni-purpose technologies have become multifunctional: both telephones and word processers now come in forms that enable multimedia interpersonal communication (e.g. via Skype, FaceTime, email, instant messaging (IM), blogging, microblogging and others). This shift entails important behavioural changes – the learner can now be in word processing mode (writing an essay) whilst simultaneously being in communication mode (taking part in an interactive group learning session via IM or Skype): that is, multitasking.

The psychological demands that this potentially places upon the learner are not inconsiderable due to the greater likelihood of interweaving of different task types (Terras and Ramsay, 2012, 2014). Whilst the user writes a document, they may break off to answer an email or other form of social media, something that was not a consideration for the instructional designers of a generation ago. The evolution of PCs and other devices from uni-to multi-function has significant implications for how users in general and learners in particular, allocate their attention across multiple tasks. Therefore, it is to a psychologically-driven examination of the implications for pedagogically-based ‘how to’ instruction with respect to multitasking in the context of mobile learning that we now turn.

The importance of executive functioning and metacognition

Attention is a fundamental cognitive resource that enables us to engage with the environment in which we live. The changing technological landscape of this environment is placing increased demands on our limited attentional resources across a range of educational, work and social contexts; its influence on the business sector is treated by Davenport and Beck (2001). Increases in the sophistication of technology have led to increasing simultaneous use of multiple forms of media. Over the past ten years there has been a 20% increase in media use, and a 120% increase in media multitasking by American youths (Becker et al., 2013). Multitasking and distractions are commonplace. Within a three hour study period, it has been observed that students engaged in rapid switching of serial attention; for example, they spent 73 minutes listening to music and encountered an average of 35 distractions that accounted for 25 minutes of their allocated study time (Calderwood et al., 2014).

Sanbonmatsu et al. (2013) examined actual and perceived multi-tasking ability and found that people tended to overestimate their competence at multi-tasking and that this overconfidence was related to the amount of multitasking with which they engaged in everyday life. Interestingly, the participants with the best objectively measured ability to multitask were less likely to do so, while those who were less able were more likely to do so. They explained their findings with reference to the participants’ ability to control their attention and proposed that individuals may engage in frequent multi-tasking because they are easily distracted, therefore finding it difficult to concentrate on a single task. Research findings also highlight the importance of high levels of task motivation and self-efficacy which have been shown to be associated with fewer and shorted multitasking behaviours (Calderwood et al., 2014).

With respect to multitasking, recent evidence indicates a high degree of variation with a small number of individuals, so called ‘supertaskers’, highly proficient at allocating their cognitive resources across a number of tasks (Watson and Strayer, 2010). Crucially, Ophir et al. (2009) demonstrated that ‘heavy multitaskers’, namely those who frequently engage in multiple simultaneous tasks are not proficient at it, compared with ‘light multitaskers’, despite the beliefs of the former to the contrary. As our earlier discussion about the awareness of our competence to multitask demonstrates, we are not always reliably able to predict our abilities and effectively monitor and control our attention and our behaviour. Therefore, promoting metacognitive awareness is essential to support critical thinking and its transfer across contexts (Halpern, 1998). Therefore, metacognition will play an important role in the future provision of user instruction and support.

The importance of considering how cognitive resources generally, and attentional resources in particular, are challenged by new uses of technology has been explored by Carr (2011) and demonstrated by Terras and Ramsay’s (2012) discussion of the cognitive challenges encountered by mobile learners. These challenges include the importance of executive functioning, metacognition and self-regulation in order to deploy the limited pool of cognitive resources to meet the demands of mobile learning. Given that attention and executive functioning play a major explanatory role in traditional theoretical explanations of time, most notably the Attentional Gate Model (Zakay, 2000), it is likely that these mechanisms also support the ability to monitor and make temporal judgements in virtual contexts (Terras and Ramsay, 2014).

As well as considering the actual cognitive processes themselves, it is also necessary to consider our awareness of these processes – our metacognition. The importance of metacognition has previously been demonstrated and this is especially relevant with respect to understanding the temporal context. There is a need to consider both physical (objective) time and psychological (subjective) time (Terras and Ramsay, 2014). Physical time is linear, continuous and measured in the standardised units such as seconds, hours and days. Psychological time is non-linear, discrete and unique because it is context-dependent (Zakay, 2012). Furthermore, an appreciation of the experiential dimension of time and the psychological infrastructure that supports our temporal abilities may offer insight into issues concerning immersion and flow and impact on time spent on learning activities (Terras and Ramsay, 2014).

A detailed characterisation of the challenges should also be considered within the context of the psychological enablement that is available to meet or manage these challenges. One might consider this in terms of the ‘psychological infrastructure’ that supports e-learning. This infrastructure comprises three elements: (1) a finite set of cognitive resources is available at any one time; (2) metacognitive ability determines e-learning success; and (3) individual differences influence e-learning outcomes (Terras and Ramsay, 2014). Multitasking across a range of technology is frequent and is likely to become common practice as technological sophistication improves and becomes further embedded into our lives. Therefore, next generation user instruction will need to help users manage these competing demands on their time and cognitive resources as a major component of instruction on how to learn.

As noted in our earlier discussion of transfer, learners are now being asked to use a device that is primarily associated with social use for learning. Users must be able to recognise and manage the different uses – in short, they are required to multitask using the same device. More importantly they need to be able to inhibit inappropriate uses of the device, for example using their phone for social purposes while engaged in study. Using Facebook as a case study, Facebook use by students is associated with increased task-switching and multitasking during self-directed learning (Judd, 2014). Studies of traditional in-class multitasking also illustrate the detrimental effect that multitasking involving Facebook and texting during class has on academic performance (Junco, 2012). Facebook use also functions as a distractor in self-study settings where it is again related to lower academic achievement (Rosen et al., 2013). Learners therefore need to be aware of the detrimental effects of multitasking and may require instruction in how to manage it. For example, Rosen demonstrated that the active use of study strategies helped learners avoid distractions and recommended the provision of ‘technology breaks’ and teaching students metacognitive strategies (Rosen et al., 2013).

User-generated instruction: consumers turned producers?

The future development of user instruction must recognise the rise and popularity of user-generated content. We use the term ‘user-generated content’ to describe content that has been created and disseminated on the web by non-specialist or non-expert users. Such content may be textual in the form of webpages, weblogs, twitter feeds, online discussions, images, videos that form a YouTube stream, or a video weblog, to name just a few possibilities. In particular, Web 2.0 has enabled the uptake of YouTube as a frequently-used means of learning how to use software. The increasing proliferation of user generated instruction is interesting as it clearly demonstrates that individuals recognise and value the need for guidance across a range of tasks, be they of a practical, educational, or other nature. Experiences are shared by capitalising on the range of user-generated opportunities for content creation that Web 2.0 technology affords. This is a prime example of a user-driven shift in user instruction, reflecting a move away from provider driven instruction to user generated instruction that is situated and reflects its ecological context of use. Providers are also capitalising on the advantages of technology to support access to materials at a learner’s convenience with many text books providing ancillary sites and textbooks being supplemented with ‘how to’ videos.

Mobile technology allows ‘how to’ instruction to be delivered in context. Learners can learn from mobile instruction created by their peers i.e. other learners, and with the camera taking the perspective of the user. Such free-to-use, ad hoc, informal instruction can be viewed as many times as desired, and a direct line of communication to the creator and a community of other peers seeking similar guidance is also generally available. Instruction that has been created by one’s peers has, by its very provenance, an arguable degree of authenticity and authority that drives its uptake. In this way, contemporary Web 2.0 platforms are enabling learners to become instructors, thus blurring traditional, established distinctions between the two roles and activities. Whilst the democratisation of the creation of user guidance and support is a welcome development as it engenders the creation of multifarious forms of highly accessible support for myriad ‘how to’ queries, it nevertheless will only be truly maximised if the considerations that we raise next are observed. We now set out our proposals for a reconceptualization of user guidance and support for 21st century learning requirements.

A 21st century reconceptualization informed by Marr’s Levels of Analysis

We have chosen to use a classic framework developed in the early 1980s, to structure our conceptualisation of 21st century user instruction and support. We have chosen David Marr’s (1982) Levels of Analysis as our organising framework because it has stood the tests of both time and application: it has been very widely applied as a robust framework for making explicit the different forms of activity and levels of explanation that might be involved in understanding a complex system. Originally proposed to inform the development of a computational visuo-perceptual system by understanding the human visual perception system, Marr’s multi-dimensional analysis approach can be used to conceptualise complex systems more generally. By adopting Marr’s levels of analysis framework, we recognise the significance, quality and influence of the research effort carried out in cognitive science one generation ago and from which we continue to benefit. Although we note that Marr’s original framework has most recently undergone some conceptual development with respect to the visual system (Poggio, 2012), it is the original framework that we now use here as the multi-dimensional level of analysis provides the finer grain exploration and specification required for our reconceptualization of ‘how to’.

In brief, Marr’s framework comprises three levels of analysis:

Computational (what needs to be solved?).

At this level of analysis the task needs to be specified. In other words, what does the system need to do?

Algorithmic (how can it be achieved?).

At this level, the means by which the system achieves its goals must be specified. For our purposeshere, we consider this level of analysis as drawing upon those theories, models and insights from theresearch base that inform our thinking.

Implementational (how can it be delivered/physically realised?).

At this level realisations of how goals can be achieved are set out. To clarify, at this level we willconsider concrete and specific instantiations of how the previous two levels might be rendered inpractical, everyday, usable form.

We now use Marr’s three level framework to present our view of the future of user guidance and support.

Level 1: what needs to be solved? (Computational level)

User instruction and support for 21st century learning purposes must support the following learner activities. Users and learners require support to manage the demands of the changing spatio-temporal dimension of mobile learning and an associated metacognitive awareness of the changing contexts of self and others as they make demands of limited cognitive resources. Support for contextual change reflects the move from reductionist to holistic support with 21st century user guidance and support for the multiple concurrent tasks that learners engage in. Users in general and learners in particular will need to be aware of their contexts of learning and self-regulate both their behaviours and their processing resources. To this end, user instruction and support for 21st century learning purposes must facilitate the development of superior metacognitive ability. Lastly, new forms of support are required to support learners in their ability to select and use, and to also create their own user-generated content.

Level 2: how can it be achieved? (Algorithmic level)

21st century user instruction should promote context awareness and the need to be sensitive to the states of other learners within it. This is paramount in the area of mobile learning where the context of the learners may change during the course of the interaction. Such contextual changes have implications for learning and the support for learning. The aesthetic appeal and strong affordances of current day mobile devices is the specific legacy of reductionist human-computer interaction research. However, this ease of use might now deceive learners (and in some instances educational providers) into believing that they are well equipped to use their devices to learn. We argue here that they are not: the challenge now is to become aware, as a learner, that one inhabits a shared and shifting digital learning space. As such, one needs to self-regulate and be aware of the needs and contexts of other learners if one is to truly maximise the constructivist potential of Web 2.0 as a learning platform.

The challenge has shifted from which buttons to press (one either did or did not know) to knowing ‘how to’ use the device but – and this is of great significance – knowing how to behave appropriately and effectively in shifting contexts. In other words, the challenge is no longer reductionist in nature, rather, it is holistic. A generation ago, user instruction dealt in the non-negotiable currency of “which buttons to press and which menu items to choose”. One generation on, the currency of user instruction is more qualitative in essence: it concerns the manner in which one behaves. Consequently, one can offer user instruction in maximise one’s learning whilst mobile and how to manage and respect the changing contexts of one’s own learning and those of others, yet there is no way of enforcing this. We are asking mobile learners to sign up to a voluntary metacognitive code. In the same way that people need to be mindful of self and others in shared public spaces, the same applies in online learning spaces.

This, together with the limited nature of our information processing resources and the increased demands of multitasking and contextual monitoring, adds additional strain. In theory, these cognitive constraints could be addressed in two ways: extend capacity and/or minimise the processing requirements of the task. In practice, attempts to develop our resources, especially working memory capacity have been largely unsuccessful (Melby-Lervåg and Hulme, 2013). More success has been achieved in terms of learning design that reduces cognitive load. We therefore propose that longstanding emphasis, which has traditionally been placed on the design of material that is sensitive to cognitive constraints, is maintained.

The most well-known and influential approach is that of Sweller (1988) who uses the concept of cognitive load to reflect the limited nature of our processing resources. Load-based theories of instructional design are of relevance here because they help to identify the source of the demands and offer ways in which the load may be reduced. In general, overload occurs when the processing demands of a task exceed the cognitive resources, especially the working memory that is available. Hence, load-based theories of instructional design for learning aim to minimise overload in the presentation of learning resources.

Cognitive load is a useful concept because it is multifaceted and there are three types of load – intrinsic, extraneous and germane – with each type of load being derived from a different source. Intrinsic cognitive load reflects the processing resources required to complete the task and is inherent in the task. Germane load reflects the working memory resources required and extraneous cognitive load reflects external demands. The major objective of load-based design is to minimise extraneous load to allow our limited resources to be directed to the task at hand. Traditionally extraneous load reflected demands within the instructional materials themselves. Reconceptualised instructional materials for 21st century learning may benefit from extending the remit of extraneous load to include wider aspects of the context in which the learning occurs, the learning platform and the skills and preferences of the learner.

The need to be aware of one’s own learning within context and that of others within contexts shared and non-shared requires strong metacognitive ability. This can be addressed through a redirection of user instruction away from support for procedural information to self-regulation. Lazonder (2001) developed a minimal manual that supported self-regulation when conducting web searches. When compared with a minimal manual that offered procedural instruction, the time spent practicing was longer for the self-regulation manual and the search performance did not differ significantly. As Lazonder observes, the ability to manage one’s search and information retrieval behaviour is more important than procedural information regarding how to search.

More recently, Zap and Code (2009) looked at self-regulated learning in computer gaming; Hu and Zhuang (2011) have explored the development of ways of promoting metacognitive ability in mobile learners; Agostinho and colleagues (Agostinho et al., 2011) have developed a computer-based tool for managing cognitive load; and, more recently still, Roodenrys et al. (2012) have shown that it is possible for students to develop the ability to manage their split attention. These and other research efforts point to a growing appreciation of the need to regulate one’s self when learning whilst mobile.

We propose that there are three major ways in which this can be achieved, namely through the removal of a number of psychological barriers, the development of media literacy and a change of culture. Metacognition has been identified as playing a central role in the regulation of our cognitive processing in mobile learning (Terras and Ramsay, 2012, 2014). Just as we regulate our behaviour in traditional learning contexts, we need to regulate our behaviour in the online context. However, as noted earlier, this is more difficult. One cannot fly an aircraft without receiving formal user instruction, either via classes, using a simulator, or referring to a manual, or indeed by using all three. One generation ago, we could not use a computer without referring to the manual or being shown by someone else. Therefore, manuals, minimal or otherwise, played a central role in ‘how to’.

The next generation of user guidance and support must offer the user ways of making sure that learners exercise good judgment about the sources of information they use. Although it is important for students to know ‘how to’ use technology to learn, it is essential to remember that any newly-conceptualised pedagogically-driven ‘how to’ instruction retains solid educationally-driven guidance in key learning and thinking skills. This educationally-grounded advice must also be updated for 21st century contexts of learning where the increasing availability of user-generated content with unknown accuracy offers additional challenges to learners. The possession and appropriate application of digital literacy skills is essential for e-learning (Terras and Ramsay, 2012).

The earlier discussion of less and more experienced users assumes that basic skills in how to use technology will transfer across contexts. Skill transfer is an area that our proposed reconceptualisation of user instruction can address. The significance of transferable media literacy skills has been identified as central to this (Terras and Ramsay, 2012; Terras et al., 2011). Despite engaging in a range of content creation related activities in the social domain such as Twitter and YouTube, the production of educationally-orientated materials online has been met with less enthusiasm (Terras et al., 2013). Our proposed fine-grained distinction between a skills-based competency in how to use technology generally, together with the more specific understanding of pedagogically-based instruction in how to use technology, may offer insight by informing future research.

Level 3: how can it be delivered? (Implementational level)

How might this new 21st century user instruction be implemented? Any reconceptualization of user instruction should be informed by current behavioural interaction with technology. Firstly, the nature of learning in the 21st century is firmly interactive and enabled by the very nature of the internet which allows one-to-many-to-one communication on a global scale. The second major force is the active construction of new content (user-generated content) by both individuals and groups (Collis, 2005; Collis and Moonen, 2002, 2006). It is these two major and conjoint elements that need to be both harnessed and exploited, if effective user guidance and support is to be delivered. These two forces will breathe life into the nature and form of new types of user guidance and are reflected in our proposals. The overarching interactive and constructive nature of things to come necessarily directs ‘how to’ away from guidance laid down by experts in the ‘How To’ Manuals of a generation ago – whether comprehensive or minimalist – towards forms of generative, ad hoc, situated in-the-moment support for appropriate reflective (i.e. metacognitive) behaviour.

This support might well be user-crafted. It might come in the form of widgets if the user has user interface design skills, or it might come in the form of uploaded text written for a specific purpose. To a certain extent, the baton of ‘how to’ has been passed from developer to user/learner. However, the most exciting but most challenging of all new forms of ‘how to’ may come in the form of ways to develop our awareness, responsiveness and sensitivity to others with whom we engage online (metacognitive function) and ways of planning our time and effort online (again, metacognitive function). To reiterate the argument that we advanced at the outset, we no longer need to know ‘how to’ in its original operational sense from a generation ago. Rather, we now need to know ourselves; i.e. how to behave for the purposes of effective and appropriate communication online. With this in mind, we anticipate that guidance in ‘how to’ in the 21st century, using new forms of online communication, may take, if not the exact form of the following, then perhaps reflect the more general spirit of it.

Beginning firstly with support for the awareness of spatiotemporal changes of self and others, this might potentially be signalled via simple within-application icons or earcons that are indicative of the user’s physical location. Information that communicates the state or status of self and other parties might be communicated in simple textual form – e.g. ‘Outside’ or ‘Inside’ or ‘Own environment’ or ‘Public Space’ – to indicate the potential for interruptions. Icons might also signal how amenable to interruptions one is through an availability manager of the type commonly used in pioneer applications such as BellCore’s Cruiser system (Root, 1988) and CUSeeMe in the early 1990s and, more recently, Skype.

A comprehensive literature exists on presence and ambient awareness management from the early 1990s (Abel, 1990; Fish, 1989; Fish et al., 1993; Heath and Luff, 1991; Ramsay et al., 1996; Whittaker, 1995) through to the present day (Hodges et al., 2012; Lim et al., 2010) together with instantiations that are commonly available via social media updates and microblogging. For our specific purposes here, the signalling of the following is central: the number and ascribed significance of a user’s ongoing tasks to communicate how busy he or she is, what they are currently occupied with, potentially including their state of mind – for example, serene or otherwise.

Indeed, in the 1990s research into ‘tangible user interfaces’ (TUIs) (Ishii and Ullmer, 1997) was already underway, demonstrating the potential for networked personal objects in the physical world to suggest an ambient awareness of one’s physical context to others, thus providing a link between the online world and the offline context. Recently, in a review of TUIs, Shaer and Hornecker described the power of TUIs aptly as ‘allowing users to quite literally grasp data with their hands’ (Shaer and Hornecker, 2010: 4). While user interface design clearly has the potential to go part of the way towards supporting an interpersonal awareness of interlocutors’ states, locations and levels of task absorption and interruptibility, the real gains are to be won though a change of mindset, expectation and behaviours in communities of online users.

Rather than expecting everyone to be ‘always on’ and therefore interruptible and available, there needs to be a culture change for the new century. We call for a culture that has at its core the understanding that the needs, habits and behaviours of other online users are potentially quite different from one’s own (Terras and Ramsay, 2012, 2014) and that this should be both expected and respected. Indeed, this can only be delivered properly if mechanisms are in place that provides guidance on how to look for this, recognise and respond to it. We offer some suggestions for realising this in our third topic below, where we consider metacognition in more depth.

While much user guidance, where it concerns the feasibility or permissibility of contacting or interrupting other parties, might be communicated via a common user interface as outlined previously, there looms the more complex challenge of finding effective ways of being mindful to the states, needs and preferences of others. One’s metacognitive function also covers the planning, management, monitoring and evaluation of activities, something that is gaining in importance as learning activities increasingly take place online within communities of learners across different time contexts (Terras and Ramsay, 2012, 2014). Clearly, the possibility exists of developing other mechanisms to assist users in developing their metacognitive function. Whilst there is certainly the opportunity for user interface features such as appointment and task reminders and various alerts to support users in organising and planning their time online, these technical solutions do not address the behavioural challenge of supporting users in becoming more adept at planning their activities online.

Our treatment of the first challenge, support for the awareness of spatio-temporal changes of self and others, indicated that holistic, metacognitive support is required there too. Even when the user interface indicates a particular state of availability (or otherwise) of another party, this information needs to be complemented by a rounded appreciation that other parties can be expected to have different personalities, personal preferences, local arrangements, physical contexts, time constraints and different concurrent demands placed upon them. One proposal for support for developing an appreciation of the worlds of others may come from research into the development of the Theory of Mind Mechanism (Leslie et al., 2004), which allows one to comprehend that other people have wants and intentions that are different from one’s own (Frith and Happé, 1999; Wimmer and Perner, 1983). Research suggests that it is possible to improve one’s theory of mind – for example by reading works of fiction (Kidd and Castano, 2013).

Alternatively, a number of considerations have been put forward for the development of sociability and online trust (Feng et al., 2004; Preece, 2000, 2001). In particular, Preece (2000) suggests a number of determinants of online sociability that are anchored in people, purpose and policies. This can be complemented with new insights from other spheres such as that of Levine and Crowther (2008) that suggest that it is possible to overcome or weaken a number of hitherto well-established group behaviour effects such as the bystander effect (Darley and Latané, 1968). More recently, factors that influence responsiveness to others have been investigated in online contexts: Van Bommel et al. (2012) found that variously highlighting the participant’s name in red on the screen and also making participants aware of a webcam in online chatrooms reversed the bystander effect. While this latter finding clearly concerns the likelihood of intervening in a perceived plight, at a broader level this can be interpreted as self-awareness cueing appearing to increase one’s likelihood of being attentive to and acting upon the states of other individuals online. It is to the broad sphere of the aforementioned research programmes that the ‘how to’ effort should now turn, in order to develop mechanisms that support individuals in being aware of and responsive to the needs to others online.

Conclusion: the future

In this paper we have characterised the nature of the next generation of user instruction and support for 21st century online learning behaviours. We have reflected upon the concept of user instruction and its role in helping individuals to interact with computers twenty five years ago and considered the nature and form of comparable support for current technology-related behaviours. With a trans-generational dialogue in mind, we have adopted a classic framework from that time (Marr’s 1982 Levels of Analysis) to organise our thinking to allow a reconceptualization of user guidance for the new century. Our proposed reconceptualization of user instruction will hopefully inspire and guide the development of future forms of user support as the pendulum swings towards situated, interactive and mobile-device use that is reliant upon user-generated guidance and a mindful awareness of the states and intentions of others in the 21st century.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Author Biographies

Dr Judith Ramsay is a Chartered Psychologist and an Associate Fellow of the British Psychological Society. Judith is a Senior Lecturer in Psychology at Leeds Beckett University, UK. She has worked in Scotland, England, Germany and Denmark in both academia and industry, researching human–computer interaction. She has published extensively in the field of computer-mediated communication behaviours, e-learning and mobile learning.

Dr Melody M Terras is a Chartered Psychologist and an Associate Fellow of the British Psychological Society. Melody is a Lecturer in Psychology at the University of the West of Scotland with research interests in the areas of cognitive psychology, reading and dyslexia, learning disabilities and educational technology.

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The pendulum swing of user instruction and interaction

Abstract

Keywords

Introduction

A Heideggerian perspective on ‘how to’ and ‘in order to’

The psychological perspective on learning how to use

Re-contextualising ‘how to’ for the 21st century

Support for new contexts of learning – a case study

The evidence that underpins our reconceptualization of ‘how to’

E-learning contexts: the spatio-temporal dimension

The uni-function to multi-function shift: opportunities and challenges

The importance of executive functioning and metacognition

User-generated instruction: consumers turned producers?

A 21st century reconceptualization informed by Marr’s Levels of Analysis

Level 1: what needs to be solved? (Computational level)

Level 2: how can it be achieved? (Algorithmic level)

Level 3: how can it be delivered? (Implementational level)

Conclusion: the future

Footnotes

Funding

Author Biographies

References