Review of Using Concept Mapping as Assessment Tools in Science Education

• In Event: Exploring the Frontiers and Linking Critical Aspects of Assessments in Science

Abstract

Concept mapping (CM) has a unique strength in assessing students’ knowledge structure and it has been recommended as a type of assessment for inclusion in the framework of National Assessment in Educational Progress (Fu, Raizen, & Shavelson, 2009). This paper reviews studies on CM assessment after landmark review in 1996 (Ruiz-Primo & Shavelson) and is intended to provide an update and consequently suggestions for future educational research and practice.

Despite the great potential of CM assessment, Ruiz-Primo and Shavelson (1996) found CM was infrequently used and suggested more studies were needed to systematically examine it. Since then, CM assessment has been more widely studies in many science areas, such as chemistry (Kaya, 2008), biology (Preszler, 2004), and physics (Ingec, 2009). CM assessment has many varieties based on task, response format, and scoring system (Ruiz-Primo & Shavelson, 1996). The development of new technology has facilitated the progress in CM use and research, e.g., softwares have been developed to help concept map construction (Schaal, Bogner, & Girwidz, 2010), scoring (Herl, O'Neil, Chung, & Schacter, 1999), and feedback-giving (Conlon, 2006).

The literature were collected from three major resources: (a) Electronic databases searches using relevant key words (e.g., “concept map” and “science”), such as ERIC and PsycInfo; (b) major science education journals, and (c) “snowball” methods—seeking additional articles from critical ones via the cited reference search or reference lists. We applied the following inclusion criteria: studies that (a) are published in peer-reviewed journals or books; (b) use concept map as an assessment tool; (c) are reported as a published article in 1996 or later.

We developed an analytical coding system to help analyze each article for further quantitative and qualitative synthesis. The major dimensions of the coding system are as follows:
• Context of usage: e.g., subject, specific topic, grade level, type of students
• Characteristics of CM: task, response format, and scoring system
• The function of the CM: e.g., as formative or summative assessment tool
• The use of technology in CM: e.g., construction, scoring, and feedback giving
• Technical quality of CM: all types of reliability and validity

Currently we are coding the articles collected, we will identify and summarize patterns and trends after the coding is completed. We will answer various questions such as: What types of constructs have been measured? What roles has technology played in the usage and research of CM assessment? How frequently CM is used as formative and summartive assessment tool? What particular tasks, response formats, and scoring systems have been used and which ones have a better technical quality than others? Finally, we will evaluate how well the problems and issues raised 15 years ago have been addressed and suggest the remaining and new problems and issues.

This study will enrich our knowledge about CM assessment by systematically reviewing the related research in the past 15 years. It helps identify the achievements, challenges, future directions, and practical strategies of using CM as an assessment tool in science education.

Author

• Yue Yin, University of Illinois at Chicago