Mobile devices are a relatively new phenomenon; this raised the question as to whether any research has been conducted to investigate their performance as educational tools in terms of cognitive load. From an HCI perspective, one could hypothesise that there will be an increase in cognitive load compared to a non-computer-based learning activity, but one could also hypothesise that the advantages afforded by the devices may off-set this potential barrier to learning. This is not just an important question from an
educationalist-perspective, but also from a software-development perspective. If the high production costs and development-time (Chapman, 2006) related to mobile application design do not result in a beneficial change in learning outcomes it may require a re-think as to how these devices are best used.
With these factors in mind, a thorough search of the social science and computer science databases was undertaken. This search revealed no published experimental studies comparing cognitive load in learners using tablet devices, with that found in learners using traditional non-digital learning materials. There were, however, a number of published papers that looked at m‑learning from a cognitive-load perspective, and a subset of these considered equipment design. The limitations of these papers that may implicitly suggest the need for further research are listed below
The few device-comparison studies in evidence were mostly from a screen-size
perspective (Findlater and McGrenere, 2008; Kim and Kim, 2012; Raptis, et al., 2013) and two of these studies used simulations rather than mobile devices which compromised ecological validity, and in one case technical equivalence. One study looked at cognitive load relating to touch screens (Ando and Ueno, 2010) but this study only considered data input methods (specifically, the ability to write the Japanese character-based alphabet on a touch-screen). At least one paper identified device issues that did not relate to the device, but rather the software (Gikas and Grant, 2013). Several studies compared touch- screen devices with desktop computers from various viewpoints, but not strictly using CLT (Findlater and McGrenere, 2008; Molina et al., 2014). Lack of data relating to m‑learning hardware was also identified in 2013 by Raptis et al., who note that previous research
tends to focus on user experience rather than the unique inherent physical attributes of the device. In summary, there is little published evidence to suggest that the mobile- device hardware has been assessed from a CLT viewpoint.
2.7.1. Explicit Recommendations for Further Research Made in The
Literature
In addition to the implicitly suggested need for further research from the limitations outlined above, some of the papers reviewed made explicit recommendations. Hollender et al. (2010), and Schmidt-Weigland and Scheiter (2011) proposed that the increasing complexity of virtual learning environments is likely to impact adversely on the cognitive load of the learner and Hollender specifically identifies the need for further research in this area.
Terras and Ramsey (2012) identified five challenges that are specific to m‑learning four of which relate to cognition, namely; the context-dependent nature of memory, the finite
nature of human cognitive resources, distributed cognition and situated learning and metacognition being essential for m‑learning. The authors cite CLT as playing a key role in informing the design of m‑learning materials. This is due to the fact that extraneous cognitive load may be heavy in m‑learning environments, and developers must take this into account. Mayer’s Cognitive Theory of Multimedia Learning is identified as a resource that should be used as a guide in creating learning materials that “provide the richness of face to face learning while delivering it over a lean and mobile medium” (Mayer, 2009 p.825). Raptis et al. (2013) identified the need to conduct further research on tablet devices from a screen size perspective. Alsherhri, Freeman and Freeman, (2013)
compared three mobile phones regarding the cognitive load imposed by their operating systems and suggested the need for further research into CLT associated with mobile devices as determined by the environment in which they are used. Similarly, Sung and Mayer (2013) Identified the need to look at m‑learning in different environments.
to participate in the research (Kim and Kim, 2012; Martin and Ertzberger, 2013; Molina, et al., 2014; Raptis et al., 2013). While this offers convenience to the researcher, it may not present a representative sample of distance learners, in a recent demographical survey, 61% of online learners were over the age of 30 years (Aslanian and Clinefelter, 2012). This suggests the need to conduct research on a wider age-group of m-learners. This need was echoed by Liu, Li and Carlsson (2010) who stated that it would be helpful if further
research were conducted to investigate m‑learning adoption by users of different age groups.
In Summary, this review has shown that there is a body of research to indicate that Mobile devices are uniquely equipped to reduce cognitive load in the learner if the
learning materials are constructed according to the principles of good instructional design as informed by CLT. However, in the field of HCI, there has also been much written about the potential for an increase in cognitive load seen when users are required to interact with a computer. This is why CLT and HCI are both are founded on the same theories of cognition (Gagné, 1985).
Hollender, et al. (2010) identified the fact that extraneous cognitive load can be divided into two broad types when undertaking computer-based learning activity. There is the ECL generated by the instructional design of the learning materials, but there is also additional extraneous cognitive load imposed by the interaction between the learner and the computer.
Figure 2-5: (after Hollender et al., 2010; van Merriënboer and Sweller 2010) Proposed ICL and ECL in m-learning
Figure 2-5 shows that ICL and ECL are additive, ECL can be increased by human-computer interaction (task load), If ICL and ECL exceed the capacity of the working memory,
germane resources cannot be employed in the formation of schemata. This diagram compares the hypothetical effect of an optimised non-computer-based learning activity on germane resources available to the learner, compared to a similar activity undertaken on a computer.
The Hollender study (2010) looked at human-computer interfaces but was published before the wide adoption of m‑learning devices such as tablet computers. This study featured an extensive systematic review of existing published literature and, as such, gives a comprehensive overview of the research at the time. With the exception of screen size, all of the studies analysed the software design rather than equipment design but there were some findings relevant to m‑learning, particularly relating to multi-modal learning. This is where a device is equipped to permit learning through multiple sensory channels. In the case of traditional computing, this is usually confined to sound and vision. Mobile devices can extend multimodality to the sense of touch, as they are equipped with a touch sensitive display not commonly found on desktop computers. However, Conway and Christiansen (2005) indicated that when looking at the effect of sensory modalities on learning the sense of touch has been virtually ignored – this still appears to be the case. Furthermore, mobile devices afford situated learning. This aspect of m‑learning is known to increase student engagement (Huizenga et al., 2009),
encourage informal learning (Chen and Huang, 2012) and provide authenticity to learning that may not be achievable in the classroom (Klopfer, Squire and Jenkin, 2008). All of these attributes can have an effect on cognitive engagement either positive or negative. Taking all of these studies into account, it is proposed that there is a need to investigate cognitive load from a purely device-related perspective. By controlling variables such as software design, material design, and situational context, it will be possible to assess whether the use of the touch-screen device itself has any effect on cognitive load. The proposed study, is, therefore, an experimental two-armed trial to investigate the task
load placed on the learner when undertaking an educational activity on a touch screen device. In consideration of a suitable control against which to test the device, there have been a number of published studies designed to compare mobile devices with personal computers or laptops, but this may no longer be a relevant comparison. Mobile devices were a new phenomenon in the early 2000s, and it might have seemed logical to compare them with the available contemporary technology to determine whether they could be used instead of, or as an adjunct to personal computers. It could, however, be considered that there has been a paradigm-shift away from computers that makes such a choice irrelevant. We are living in the so-called Post-PC era, declared by Steve Jobs at the launch of the iPad and reiterated by his successor Tim Cooke at the launch of the iPad Pro (Gilbert, 2015). This is an era in which smartphone adoption outstrips PC use by more than 10 to 1 (Heggestuen, 2013; Ericsson, 2015) and in which half of UK households now possess a tablet PC (OFCOM, 2015). In a recent market-share forecast by the International Data Corporation (IDC) it is predicted that by 2017, smartphones and tablets will take 87% of the worldwide market share for connected devices, leaving PCs with just 5% and
laptops with 8% of the market share (Shirer, 2015). Personal computers and laptops simply do not have the ubiquity that is desirable for m‑learning. Furthermore, these devices are not equipped for m‑learning environments as they are typically not connected to mobile networks. Very importantly, they lack the one essential factor needed for any-time, any-place learning – they are not hand-held. At the time of their conception, tablet computers were not intended to replicate or replace computers. Kay (1972) had a very specific concept for the device that was intended to go into production at Xerox Computers, tellingly, the name he gave it was the Dynabook. It is therefore suggested that this study should go back to first principles, and look at how learning on a mobile touch-screen device compares against the most appropriate comparator for any-