Prediction Ability of College Students in Solving Graph Problems
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| Title: | Prediction Ability of College Students in Solving Graph Problems |
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| Language: | English |
| Authors: | Lathifaturrahmah Lathifaturahmah, Toto Nusantara, Subanji Subanji, Makbul Muksar |
| Source: | Mathematics Teaching Research Journal. 2024 15(6):59-73. |
| Availability: | City University of New York. Creative Commons. 205 East 42 Street, New York, NY 10017. Web site: https://commons.hostos.cuny.edu/mtrj |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Mathematics Instruction, Mathematics Skills, Prediction, COVID-19, Pandemics, Problem Solving, Teaching Methods, Graphs, College Students, 21st Century Skills, Foreign Countries |
| Geographic Terms: | Indonesia |
| ISSN: | 2573-4377 |
| Abstract: | The capacity to generate prediction is indispensable in daily existence, particularly amidst the swift transformations that are occurring on a global scale. Therefore, this study aimed to analyze the levels of prediction ability among mathematics students when presented with data in graphs. A qualitative approach was adopted, involving 37 mathematics students, using taskbased tests and interviews as data collection techniques. The results showed that the ability of most students to make a prediction based on the COVID-19 graph was at a multi-structural level of 35.14%. This level was characterized by students making predictions based on the trends of the pandemic graph patterns, but they tended to overlook the overall patterns. The prediction generated at the unistrutural, multistructural, relational, and extended abstract levels was considered reasonable because of the graph or data provided. These findings indicated the existence of predictive reasoning conducted by students in making predictions of problems related to the COVID-19 graph. The insights gained into the prediction ability prompted teachers to enhance graphic literacy instruction, to equip students with the skills needed to thrive in the 21st century. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1417808 |
| Database: | ERIC |
| Abstract: | The capacity to generate prediction is indispensable in daily existence, particularly amidst the swift transformations that are occurring on a global scale. Therefore, this study aimed to analyze the levels of prediction ability among mathematics students when presented with data in graphs. A qualitative approach was adopted, involving 37 mathematics students, using taskbased tests and interviews as data collection techniques. The results showed that the ability of most students to make a prediction based on the COVID-19 graph was at a multi-structural level of 35.14%. This level was characterized by students making predictions based on the trends of the pandemic graph patterns, but they tended to overlook the overall patterns. The prediction generated at the unistrutural, multistructural, relational, and extended abstract levels was considered reasonable because of the graph or data provided. These findings indicated the existence of predictive reasoning conducted by students in making predictions of problems related to the COVID-19 graph. The insights gained into the prediction ability prompted teachers to enhance graphic literacy instruction, to equip students with the skills needed to thrive in the 21st century. |
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| ISSN: | 2573-4377 |
