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Do Written Responses to Open-Ended Questions on Fourth-Grade Online Formative Assessments in Mathematics Help Predict Scores on End-of-Year Standardized Tests?

Predicting long-term student achievement is a critical task for teachers and for educational data mining. However, most of the models do not consider two typical situations in real-life classrooms. The first is that teachers develop their own questions for online formative assessment. Therefore, the...

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Detalles Bibliográficos
Autores principales: Urrutia, Felipe, Araya, Roberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9624346/
https://www.ncbi.nlm.nih.gov/pubmed/36278604
http://dx.doi.org/10.3390/jintelligence10040082
Descripción
Sumario:Predicting long-term student achievement is a critical task for teachers and for educational data mining. However, most of the models do not consider two typical situations in real-life classrooms. The first is that teachers develop their own questions for online formative assessment. Therefore, there are a huge number of possible questions, each of which is answered by only a few students. Second, online formative assessment often involves open-ended questions that students answer in writing. These types of questions in online formative assessment are highly valuable. However, analyzing the responses automatically can be a complex process. In this paper, we address these two challenges. We analyzed 621,575 answers to closed-ended questions and 16,618 answers to open-ended questions by 464 fourth-graders from 24 low socioeconomic status (SES) schools. Using regressors obtained from linguistic features of the answers and an automatic incoherent response classifier, we built a linear model that predicts the score on an end-of-year national standardized test. We found that despite answering 36.4 times fewer open-ended questions than closed questions, including features of the students’ open responses in our model improved our prediction of their end-of-year test scores. To the best of our knowledge, this is the first time that a predictor of end-of-year test scores has been improved by using automatically detected features of answers to open-ended questions on online formative assessments.