EXPLORING INNOVATIVE APPROACHES TO DATA MANAGEMENT IN TEACHER EDUCATION FOR EFFECTIVE STUDENT LEARNING
Abstract
This study aimed at examining innovative approaches to data management in teacher education to enhance student learning outcomes where a survey design was employed, and self-structured questionnaires were used for data collection. The questionnaire was duly validated by three experts. The sample size consisted of 87 lecturers from four tertiary institutions in Anambra state. The study addressed four research questions and two null hypotheses related to the current practices, challenges, and implementation levels of various data management strategies. Findings revealed varying levels of implementation for approaches such as utilizing student data, ongoing training for teachers, involving parents and the community, providing targeted assistance, and recognizing student diversity. These findings provide valuable insights for educators and institutions to enhance pedagogical practices through effective data management. The study highlighted the importance of leveraging data to inform instructional decisions, personalized learning experiences, and fostering an inclusive learning environment. Future researches should focus on the long-term impact of these approaches on student outcomes and explore ways to refine and expand their implementation.
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Blau, I., &Hameiri, M. (2017). Ubiquitous mobile educational data management by teachers, students and parents: Does technology change school-family communication and parental involvement?. Education and Information Technologies, 22, 1231-1247.
Davidson, E., Wessel, L., Winter, J. S., & Winter, S. (2023). Future directions for scholarship on data governance, digital innovation, and grand challenges. Information and Organization, 33(1), 100454.
Georgiou, D., Diery, A., Mok, S. Y., Fischer, F., & Seidel, T. (2023). Turning research evidence into teaching action: Teacher educators’ attitudes toward evidence-based teaching. International Journal of Educational Research Open, 4, 100240.
Hardy, I. (2022). Affective learning for effective learning? Data, numbers and teachers’
learning. Teaching and Teacher Education, 116, 103754.
Horn, I. S., Kane, B. D., & Wilson, J. (2015). Making sense of student performance data: Data use logics and mathematics teachers’ learning opportunities. American Educational Research Journal, 52(2), 208-242.
Iyengar, R., Mahal, A. R., Felicia, U. N. I., Aliyu, B., & Karim, A. (2015). Federal policy to local level decision-making: Data driven education planning in Nigeria. International Education Journal: Comparative Perspectives, 14(3), 76-93.
Jennings, A. S., & Jennings, A. (2020). Comprehensive and superficial data users: A convergent mixed methods study of teachers’ practice of interim assessment data use. Teachers College Record, 122(12), 1-46.
Kazansky, B. (2021). ‘It depends on your threat model’: the anticipatory dimensions of
resistance to data-driven surveillance. Big Data & Society, 8(1),
Lawrence, J. E., & Tar, U. A. (2018). Factors that influence teachers’ adoption and integration of ICT in teaching/learning process. Educational Media International, 55(1), 79-105.
Malott, K. M., Hall, K. H., Sheely‐Moore, A., Krell, M. M., &Cardaciotto, L. (2014).
Evidence‐based teaching in higher education: Application to counselor
education. Counselor Education and Supervision, 53(4), 294-305.
Mandinach, E. B., & Gummer, E. S. (2016).What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366-376.
Olari, V., &Romeike, R. (2021, October). Addressing ai and data literacy in teacher education: A review of existing educational frameworks. In The 16th Workshop in Primary and Secondary Computing Education (pp. 1-2).
Ramsay-Jordan, N. (2020). Preparation and the real world of education: How prospective teachers grapple with using culturally responsive teaching practices in the age of standardized testing. International Journal of Educational Reform, 29(1), 3-24.
Seifu, K. (2020). Determinants of information and communication technology integration in teaching-learning process at Aksum University. Cogent Education, 7(1),
Teng, Y., Zhang, J., & Sun, T. (2023). Data‐driven decision‐making model based on artificial intelligence in higher education system of colleges and universities. Expert Systems, 40(4), e12820.
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