Assessing students' abilities to construct and interpret line graphs: Disparities between multiple‐choice and free‐response instruments (original) (raw)
Related papers
2017
Prior graphing research has demonstrated that clinical interviews and free- response instruments produce very different results than multiple-choice instruments, indicating potential validity problems when using multiple-choice instruments to assess graphing skills (Berg & Smith in Science Education, 78(6), 527–554, 1994). Extending this inquiry, we studied whether empirically derived, participant-generated graphs used as choices on the multiple-choice graphing instrument produced results that corresponded to participants’ responses on free-response instruments. The 5 – 8 choices on the multiple- choice instrument came from graphs drawn by 770 participants from prior research on graphing (Berg, 1989; Berg & Phillips in Journal of Research in Science Teaching, 31(4), 323–344, 1994; Berg & Smith in Science Education, 78(6), 527–554, 1994). Statistical analysis of the 736 7th – 12th grade participants indicate that the empirically derived multiple-choice format still produced significantly more picture-of-the-event responses than did the free-response format for all three graphing questions. For two of the questions, participants who drew graphs on the free-response instruments produced significantly more correct responses than those who answered multiple-choice items. In addition, participants having “low classroom performance” were affected more significantly and negatively by the multiple-choice format than participants having “medium” or “high classroom performance.” In some cases, prior research indicating the prevalence of “picture-of-the-event” and graphing treatment effects may be spurious results, a product of the multiple-choice item format and not a valid measure of graphing abilities. We also examined how including a picture of the scenario on the instrument versus only a written description affected responses and whether asking participants to add marker points to their constructed or chosen graph would overcome the short-circuited thinking that multiple-choice items seem to produce.
The construction and validation of the test of graphing in science (togs)
Journal of Research in Science Teaching, 1986
The objective of this project was to develop a multiple choice test of graphing skills appropriate for science students from grades seven through twelve. Skills associated with the construction and interpretation of line graphs were delineated, and nine objectives encompassing these skills were developed. Twenty-six items were then constructed to measure these objectives. To establish content validity, items and objectives were submitted to a panel of reviewers. The experts agreed over 94% of the time on assignment of items to objectives and 98% on the scoring of items. TOGS was first administered to 119 7th, 9th, and 1 lth graders. The reliability (KR-20) was 0.81. Poorly functioning items were rewritten based on the item difficulty and discrimination data. The revised version of the test was given to 377 7th through 12th grade students. Total scores ranged from 2 to 26 correct (X= 13.3, S.D. =5.3). The reliability (KR-20) was 0.83 for all subjects and ranged from 0.71 for eighth graders to 0.88 for ni?th graders. Point biserial correlations showed 24 of the 26 items above 0.30 with an average value of 0.43. It was concluded from this and other data that TOGS was a valid and reliable instrument for measuring graphing abilities.
2008
This study examined how intermediate elementary students’ mathematics and science background knowledge affected their interpretation of line graphs and how their interpretations were affected by graph question levels. A purposive sample of 14 6th-grade students engaged in think aloud interviews (Ericsson & Simon, 1993) while completing an excerpted Test of Graphing in Science (TOGS) (McKenzie & Padilla, 1986). Hand gestures were video recorded. Student performance on the TOGS was assessed using an assessment rubric created from previously cited factors affecting students’ graphing ability. Factors were categorized using Bertin’s (1983) three graph question levels. The assessment rubric was validated by Padilla and a veteran mathematics and science teacher. Observational notes were also collected. Data were analyzed using Roth and Bowen’s semiotic process of reading graphs (2001). Key findings from this analysis included differences in the use of heuristics, selfgenerated questions, ...
Investigating Student's Abilities Related to Graphing Skill
2012
Graphs as representational tools are very important in all disciplines especially in mathematics. They are useful for summari zing sets of data, obtaining and interpreting new information from complex data. The purpose of this study is to investigate pre-service mathematics teachers' graphing skills. The participants are 32 pre-service mathematics teachers from a public university. Graphing tasks and questions corresponding to the interpreting, modeling and transforming components of the graphing skill (Kwon, 2002) were used in gathering written data and interviews conducted with selected participants. It is concluded that students have problems in modeling and transforming tasks but they can extract information from graphs so they are better in interpreting tasks.
2008
This study examined how intermediate elementary students’ mathematics and science background knowledge affected their interpretation of line graphs and how their interpretations were affected by graph question levels. A purposive sample of 14 6th-grade students engaged in think aloud interviews (Ericsson & Simon, 1993) while completing an excerpted Test of Graphing in Science (TOGS) (McKenzie & Padilla, 1986). Hand gestures were video recorded. Student performance on the TOGS was assessed using an assessment rubric created from previously cited factors affecting students’ graphing ability. Factors were categorized using Bertin’s (1983) three graph question levels. The assessment rubric was validated by Padilla and a veteran mathematics and science teacher. Observational notes were also collected. Data were analyzed using Roth and Bowen’s semiotic process of reading graphs (2001). Key findings from this analysis included differences in the use of heuristics, self-generated questions, science knowledge, and self-motivation. Students with higher prior achievement used a greater number and variety of heuristics and more often chose appropriate heuristics. They also monitored their understanding of the question and the adequacy of their strategy and answer by asking themselves questions. Most used their science knowledge spontaneously to check their understanding of the question and the adequacy of their answers. Students with lower and moderate prior achievement favored one heuristic even when it was not useful for answering the question and rarely asked their own questions. In some cases, if students with lower prior achievement had thought about their answers in the context of their science knowledge, they would have been able to recognize their errors. One student with lower prior achievement motivated herself when she thought the questions were too difficult. In addition, students answered the TOGS in one of three ways: as if they were mathematics word problems, science data to be analyzed, or they were confused and had to guess. A second set of findings corroborated how science background knowledge affected graph interpretation: correct science knowledge supported students’ reasoning, but it was not necessary to answer any question correctly; correct science knowledge could not compensate for incomplete mathematics knowledge; and incorrect science knowledge often distracted students when they tried to use it while answering a question. Finally, using Roth and Bowen’s (2001) two-stage semiotic model of reading graphs, representative vignettes showed emerging patterns from the study. This study added to our understanding of the role of science content knowledge during line graph interpretation, highlighted the importance of heuristics and mathematics procedural knowledge, and documented the importance of perception attentions, motivation, and students’ self-generated questions. Recommendations were made for future research in line graph interpretation in mathematics and science education and for improving instruction in this area.
International Journal of Education in Mathematics, Science and Technology, 2020
This study investigated the graphing skills and some affective states of middle school students about graphs by their gender, grade level, and the common graph types used in science courses. Participants’ line graph skills, self-efficacy beliefs and attitudes toward graphs, and their personal literacy perceptions about different graph types (line, bar, and pie) are explored quantitatively. Qualitative data was collected about the views of participants about graphs in general, as well as about the factors that impact students like/dislike certain graph types. Based on the findings, while participants were found to lack line graph skills, they were found to hold high self-efficacy beliefs and positive attitudes toward graphs. No significant difference among the dependent variables was found based on gender; however, grade level and graph type variables were found to impact students’ graph skills and personal graph literacy perceptions. Among the commonly used graphs in middle schools,...
Review of Graph Comprehension Research: Implications for Instruction
Educational Psychology Review, 2002
Graphs are commonly used in textbooks and educational software, and can help students understand science and social science data. However, students sometimes have difficulty comprehending information depicted in graphs. What makes a graph better or worse at communicating relevant quantitative information? How can students learn to interpret graphs more effectively? This article reviews the cognitive literature on how viewers comprehend graphs and the factors that influence viewers' interpretations. Three major factors are considered: the visual characteristics of a graph (e.g., format, animation, color, use of legend, size, etc.), a viewer's knowledge about graphs, and a viewer's knowledge and expectations about the content of the data in a graph. This article provides a set of guidelines for the presentation of graphs to students and considers the implications of graph comprehension research for the teaching of graphical literacy skills. Finally, this article discusses unresolved questions and directions for future research relevant to data presentation and the teaching of graphical literacy skills.
2014
This study examined how 12- and 13-year-old students’ mathematics and science background knowledge affected line graph interpretations and how interpretations were affected by graph question levels. A purposive sample of 14 students engaged in think aloud interviews while completing an excerpted Test of Graphing in Science. Data were collected and coded using a rubric of previously cited factors, categorized by Bertin’s (Semiology of graphics: Diagrams, networks, maps. The University of Wisconsin Press, Ltd., Madison, 1983) theory of graph interpretation. Data analysis revealed responses varied by graph question level. Across levels, students interpreted graphs in one or more of the three ways: mathematical word problems (focusing on an algorithm), science data to be analyzed (incorporating science knowledge), or no strategy. Although consistently used across levels, the frequency and usefulness of approaches varied by question level.