Using Concept Maps With Errors to Identify Misconceptions: The Role of Instructional Design to Create Large-Scale On-Line Solutions

Using Concept Maps With Errors to Identify Misconceptions: The Role of Instructional Design to Create Large-Scale On-Line Solutions

Paulo Rogério Miranda Correia, Joana Aguiar, Brian Moon
DOI: 10.4018/978-1-7998-1985-1.ch006
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Abstract

Concept maps (Cmaps) have been successfully used to make knowledge structures visible. During Cmap task elaboration, novice students are likely to suffer cognitive overload, and they might avoid coping with difficult contents staying in his semantic safe territory. The authors have developed an innovative approach using Cmaps with embedded errors applied on Sero! – a cloud-based knowledge assessment platform. This chapter presents a case study involving the current use of Cmaps with errors as an assessment task capable of identifying misconceptions about the advances of molecular biology. Undergraduate students (n=86) were asked to find the errors hidden into the propositional network. The results confirmed the task challenged the students to go beyond their safe semantic territory. Misconceptions were readily identified from the students' answers providing good insights for the development of a bespoke feedback. The current data available is enough to foresee a broad range of research opportunities to readers interested in concept mapping, instruction and learning analytics.
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Introduction

Knowledge representation is a crucial part of developing conceptual understanding. This process requires selecting and organizing relevant pieces of information retrieved from the long-term memory to create an external depiction of our mental models. Concept maps (Cmaps) have been successfully used to this aim as they can make our knowledge structures visible (Hay, Kinchin & Lygo-Baker, 2008; Novak, 2010). Cmaps are an organized set of propositions (e.g., initial concept – linking phrase → final concept) that reveal the meaning of conceptual relationships. The inclusion of linking phrases to clarify conceptual relationships makes Cmaps more suitable than other graphical organizers used to represent knowledge and information accurately (Authors, 2012; Davies, 2011). The examples below illustrate how the propositional meaning can be drastically changed with discrete modifications in the linking phrases. They represent different ways to express the conceptual relationship between ‘propositions’ and ‘meaning.’

  • Propositions – ????meaning: the linking phrase is missing.

    • o

      There is only an association between the concepts ‘meaning’ and ‘proposition’, but nothing is revealed about the nature of their relationship. There is no proposition in this example.

  • Propositions – andmeaning: the linking phrase does not present a verb.

    • o

      The use of ‘and’ creates one single concept ‘proposition and meaning’, which does not carry any meaning. There is no proposition in this example.

  • Propositions – containmeaning: the linking phrase presents only a verb.

    • o

      The verb is related to the initial concept, and a coherent message is conveyed. There is a proposition in this example, allowing us to evaluate the correctness of its content (in this case, it is correct). The verb is an essential element of the linking phrase.

  • Propositions – must containmeaning: the linking phrase presents more than a verb.

    • o

      The linking phrase can contain other elements to improve content accuracy. This example is more accurate than the last one.

  • Propositions – do not containmeaning: the linking phrase presents a verb.

    • o

      One word (not) can invert the meaning of the message. Therefore, it is necessary to wisely select the words when writing the propositions to ensure that they represent our ideas. This example presents a proposition once the message is understandable, but its content is not conceptually correct.

The semantic content present in Cmaps is valuable to reveal how the conceptual relationships are organized into our mental models. For this reason, concept mapping has been reported in the literature for organizing, sharing, and preserving knowledge (e.g., Correia, 2012; Kinchin, 2014; Novak, 2010; Moon et al., 2011).

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