Exploring the Effect of Graphical Metaphors on the Performance of Learning Computer Programming Concepts in Adult Learners: a pilot study

McKay, Elspeth

doi:10.1080/0144341990190407

Cited by 22 publications

(16 citation statements)

References 14 publications

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“…A number of investigations provide evidence to support this position (ChanLin, 1996;McKay, 1999b;Mortensen & Schwartz, 2009;Schwartz & Collins, 2008;Schwartz et al, 2006).…”

Section: Metaphorical Representationsmentioning

confidence: 82%

Metaphorical graphics aid learning and memory

Danielson

Schwartz

Lippmann

2015

Learning and Instruction

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“…A number of investigations provide evidence to support this position (ChanLin, 1996;McKay, 1999b;Mortensen & Schwartz, 2009;Schwartz & Collins, 2008;Schwartz et al, 2006).…”

Section: Metaphorical Representationsmentioning

confidence: 82%

Metaphorical graphics aid learning and memory

Danielson

Schwartz

Lippmann

2015

Learning and Instruction

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“…ChanLin 1996;Duit 1991;Gee 1978);McKay 1999;Murphy 1996;Webb 1985;Weller 1970). As one would expect, examples can be found in nearly all domains, ranging from physics (Podolefsky and Finkelstein 2006) to chemistry (Thomas and McRobbie 2001) and history (Schwartz et al 2006).…”

Section: Analogiesmentioning

confidence: 96%

A Relational Reasoning Approach to Text-Graphic Processing

Danielson

Sinatra

2016

Educ Psychol Rev

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We propose that research on text-graphic processing could be strengthened by the inclusion of relational reasoning perspectives. We briefly outline four aspects of relational reasoning: analogies, anomalies, antinomies, and antitheses. Next, we illustrate how textgraphic researchers have been conducting research aligned with aspects of relational reasoning, although not deliberately. We call for future research on intentionally designed textgraphic pairings that should be empirically tested for their ability to support relational reasoning. Finally, we argue that relational reasoning may help explain some of the mixed results and unintended outcomes that often appear in the text-graphic research literature.Researchers have developed rich models to account for both text processing (Kintsch 1992;McNamara et al. 1996) and graphic processing (Ainsworth 2006; Ainsworth and Burcham 2007; Hegarty 2011) in isolation. Yet, when text and graphics are combined, learners tend to infer very different meanings than when these representations are presented independently (Hagan 2007). Often, the combination of a text with a graphic is more than just the sum of the two parts. This is because when combined, text and graphics can communicate relationships among or between the informational representations (Hegarty 2011;McCabe and Castel 2008). In other words, text and graphics, when presented together, are inherently relational.In this article, we briefly review the extant text-graphic research as it relates to four aspects of relational reasoning: analogies, anomalies, antinomies, and antitheses. Next, we present a number of examples that draw upon these four aspects of relational reasoning as they relate to learning with texts and graphics. We go on to suggest that viewing text-graphic processing as an exercise in relational reasoning may help explain a number of inconsistent results that have historically hampered research in this area. Finally, we conclude with Educ Psychol Rev

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“…Often empirical studies investigating the usefulness of alternative approaches illustrate the variety of learners' preferences and result in identifying tendencies towards the different approaches proposed, but do not indicate obvious links between specific style categories and preferences for certain designs (Loo, 2004;Mitchell et al, 2004;Liu and Reed, 1994;Yu and Underwood, 1999;McKay, 1999;Pillay, 1998).…”

Section: Experimental Studies Investigating Learners' Style and Systementioning

confidence: 97%

“…Especially in web-based learning environments, designers also have to deal with the new medium and learning context, and use the innovative tools offered by the Internet to design alternative interactions. However, although several different approaches have been adopted, findings show only a weak link between style and learner preferences (Loo, 2004;Mitchell et al, 2004); or learning style and performance (Harris et al, 2003;Liu and Reed, 1994;Yu and Underwood, 1999); or performance and matching or mismatching to cognitive style instructional methods (McKay, 1999;Pillay, 1998;Chen, 2000, 2001;Shih and Gamon, 2002). Even if the relationship between style and learner preferences is still an open issue, experimental results suggest that learners nevertheless have preferences about the kind of interaction/presentation of information they receive, although results do not indicate obvious links between specific style categories and preferences for certain designs (Mitchell et al, 2004;Mabbott and Bull, 2004;Papanikolaou et al, 2003).…”

Section: Introductionmentioning

confidence: 96%

Designing learner-controlled educational interactions based on learning/cognitive style and learner behaviour

Papanikolaou

Mabbott

Bull

et al. 2006

Interacting with Computers

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Recently, research in individual differences and in particular, learning and cognitive style, has been used as a basis to consider learner preferences in a web-based educational context. Modelling style in a web-based learning environment demands that developers build a specific framework describing how to design a variety of options for learners with different approaches to learning. In this paper two representative examples of educational systems, Flexi-OLM and INSPIRE, that provide learners a variety of options designed according to specific style categorisations, are presented. Experimental results from two empirical studies performed on the systems to investigate learners' learning and cognitive style, and preferences during interaction, are described. It was found that learners do have a preference regarding their interaction, but no obvious link between style and approaches offered, was detected. Derived from an examination of this experimental data, we suggest that while style information can be used to inform the design of learning environments that accommodate learners' individual differences, it would be wise to recommend interactions based on learners' behaviour. Learning environments should allow learners or learners' interaction behaviour to select or trigger the appropriate approach for Interacting with Computers 18 (2006) 356-384 www.elsevier.com/locate/intcom 0953-5438/$ -see front matter q (K.A. Papanikolaou), axm891@bham.ac.uk (A. Mabbott), s.bull@bham. ac.uk (S. Bull), gregor@di.uoa.gr (M. Grigoriadou).the particular learner in the specific context. Alternative approaches towards these directions are also discussed. q

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Exploring the Effect of Graphical Metaphors on the Performance of Learning Computer Programming Concepts in Adult Learners: a pilot study

Cited by 22 publications

References 14 publications

Metaphorical graphics aid learning and memory

Metaphorical graphics aid learning and memory

A Relational Reasoning Approach to Text-Graphic Processing

Designing learner-controlled educational interactions based on learning/cognitive style and learner behaviour

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