Technology-Integrated Formative Assessment and the Predictive Role of Motivational Constructs on Conceptual and Procedural Knowledge in Chemistry
DOI:
https://doi.org/10.23887/jet.v8i2.49155Keywords:
Motivational constructs, Technology, Conceptual knowledge, Procedural knowledgeAbstract
Many countries, including Ethiopia, efforts to employ formative assessment are complicated by a variety of challenges that lead to poor practices. Technology has the ability to play a crucial role in learning-supporting formative assessment methods. However, the bulk of previous formative assessment research did not rely on technology. Therefore, this study aims to analyze the differences in motivation between the two experimental and one comparison groups, as well as the impact of five motivational predictors in learning chemistry. To achieve the purpose, a quasi-experimental pretest-posttest design was adopted. The motivation questionnaire, the chemical equilibrium conceptual and the procedural tests were utilized to collect data. One-way ANOVA and multiple linear regression analysis were used to evaluate the data. In terms of improving students' motivation to understand chemical equilibrium, technology-integrated formative assessment processes outscored conventional approaches and formative assessment strategies on their own, according to the findings. According to a significant regression equation, the five motivating components of research have a significant impact on the conceptual and procedural knowledge test scores. Individual predictors were investigated further, and it was shown that intrinsic motivation and grade motivation were both positive, significant predictors of conceptual test scores, whereas grade motivation was a positive, significant predictor of procedural knowledge test scores. Technology-integrated formative assessment procedures were shown to be more effective at increasing students' motivation to study chemical equilibrium than the other two groups.
References
Al-Wassia, R., Hamed, O., Al-Wassia, H., Alafari, R., & Jamjoom, R. (2015). Cultural challenges to implementation of formative assessment in Saudi Arabia: An exploratory study. Medical Teacher, 37(S1), S9–S19. https://doi.org/10.3109/0142159X.2015.1006601.
Almalki, M. S., & Gruba, P. (2020). Conceptualizing Formative Blended Assessment (FBA) in Saudi EFL. 65–82. https://doi.org/10.4018/978-1-7998-3062-7.ch004.
Barton, M. A., Lall, M. D., Johnston, M. M., Lu, D. W., Nelson, L. S., Bilimoria, K. Y., & Reisdorff, E. J. (2022). Reliability and validity support for an abbreviated Copenhagen burnout inventory using exploratory and confirmatory factor analysis. Journal of the American College of Emergency Physicians Open, 3(4), 1–19. https://doi.org/10.1002/emp2.12797.
Bosica, J., Pyper, J. S., & MacGregor, S. (2021). Incorporating problem-based learning in a secondary school mathematics preservice teacher education course. Teaching and Teacher Education, 102, 103335. https://doi.org/10.1016/j.tate.2021.103335.
Cheung, D. (2009). The adverse effects of le Châtelier’s principle on teacher understanding of chemical equilibrium. Journal of Chemical Education, 86(4), 514–518. https://doi.org/10.1021/ed086p514.
Darner, R. (2014). Influences on students’ environmental self determination and implications for science curricula. International Journal of Environmental and Science Education, 9(1), 21–39. https://doi.org/10.12973/ijese.2014.201a.
DeJarnette, N. K. (2018). Implementing STEAM in the Early Childhood Classroom. European Journal of STEM Education, 3(3), 1–9. https://doi.org/10.20897/ejsteme/3878.
Elmahdi, I., Al-Hattami, A., & Fawzi, H. (2018). Using Technology for Formative Assessment to Improve Students’ Learning. Turkish Online Journal of Educational Technology-TOJET, 17(2), 182–188. https://eric.ed.gov/?id=EJ1176157.
Gebre, E. (2018). Learning with multiple representations: Infographics as cognitive tools for authentic learning in science literacy. Canadian Journal of Learning and Technology, 44(1), 1–24. https://doi.org/10.21432/cjlt27572.
Gikandi, J. W., & Morrow, D. (2016). Designing and implementing peer formative feedback within online learning environments. Technology, Pedagogy and Education, 25(2), 153–170. https://doi.org/10.1080/1475939X.2015.1058853.
Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of Research in Science Teaching, 48(10), 1159–1176. https://doi.org/10.1002/tea.20442.
Goldin, I., Narciss, S., Foltz, P., & Bauer, M. (2017). New Directions in Formative Feedback in Interactive Learning Environments. International Journal of Artificial Intelligence in Education, 27(3), 385–392. https://doi.org/10.1007/s40593-016-0135-7.
González-Gómez, D., Jeong, J. S., & Cañada-Cañada, F. (2020). Examining the effect of an online formative assessment tool (Ofat) of students’ motivation and achievement for a university science education. Journal of Baltic Science Education, 19(3), 401–414. https://doi.org/10.33225/jbse/20.19.401.
Guay, F., Chanal, J., Ratelle, C. F., Marsh, H., Larose, S., & Boivin, M. (2010). Intrinsic, identified, and controlled types of motivation for school subjects in young elementary school children. British Journal of Educational Psychology, 80(4), 711–735. https://doi.org/10.1348/000709910X499084.
Hayat, A., Kohoulat, N., Amini, M., & Akbar Faghihi, S. A. (2020). The predictive role of personality traits on academic performance of medical students: The mediating role of self-efficacy. Medical Journal of The Islamic Republic of Iran, 2020. https://doi.org/10.47176/mjiri.34.77.
Jacques, L. A., Cian, H., Herro, D. C., & Quigley, C. (2020). The impact of questioning techniques on STEAM instruction. Action in Teacher Education, 42(3), 290–308. https://doi.org/10.1080/01626620.2019.1638848.
Jansen, M., Scherer, R., & Schroeders, U. (2015). Students’ self-concept and self-efficacy in the sciences: Differential relations to antecedents and educational outcomes. Contemporary Educational Psychology, 41, 13–24. https://doi.org/10.1016/j.cedpsych.2014.11.002.
Kesavan, K. P., & Palappallil, D. S. (2018). Effectiveness of formative assessment in motivating and improving the outcome of summative assessment in pharmacology for medical undergraduates. Journal of Clinical and Diagnostic Research, 12(5), FC08-FC11. https://doi.org/10.7860/JCDR/2018/34533.11527.
Laborda, J. G., Sampson, D. G., Hambleton, R. K., & Guzman, E. (2015). Guest editorial: Technology supported assessment in formal and informal learning. Educational Technology and Society, 18(2), 1–2. https://espace.curtin.edu.au/bitstream/handle/20.500.11937/23186/234047_234047.pdf?sequence=2.
Lee, H., Feldman, A., & Beatty, I. D. (2012). Factors that Affect Science and Mathematics Teachers’ Initial Implementation of Technology-Enhanced Formative Assessment Using a Classroom Response System. Journal of Science Education and Technology, 21(5), 523–539. https://doi.org/10.1007/s10956-011-9344-x.
Lin, Y. W., Tseng, C. L., & Chiang, P. J. (2017). The Effect of Blended Learning in Mathematics Course. Eurasia Journal of Mathematics, Science and Technology Education, 13(3), 741–770. https://doi.org/10.12973/eurasia.2017.00641a.
Marsh, E. J., Lozito, J. P., Umanath, S., Bjork, E. L., & Bjork, R. A. (2012). Using verification feedback to correct errors made on a multiple-choice test. Memory, 20(6), 645–653. https://doi.org/10.1080/09658211.2012.684882.
Mensah, A., & Morabe, O. N. (2018). Strategies Used by Grade 12 Physical Sciences Students in Solving Chemical Equilibrium Problems. African Journal of Research in Mathematics, Science and Technology Education, 22(2), 174–185. https://doi.org/10.1080/18117295.2018.1475908.
Nabizadeh, S., Hajian, S., Sheikhan, Z., & Rafiei, F. (2019). Prediction of academic achievement based on learning strategies and outcome expectations among medical students. BMC Medical Education, 19(1), 1–11. https://doi.org/10.1186/s12909-019-1527-9.
Ng, S. B. (2019). Exploring STEM Competences for the 21st Century. In In-Progress Reflection (In-Progres, Issue 30). UNESCO-IBE.
Nie, Y., Lau, S., & Liau, A. K. (2011). Role of academic self-efficacy in moderating the relation between task importance and test anxiety. Learning and Individual Differences, 21(6), 736–741. https://doi.org/10.1016/j.lindif.2011.09.005.
Nikou, S. A., & Economides, A. A. (2021). A framework for mobile-assisted formative assessment to promote students’ self-determination. Future Internet, 13(5). https://doi.org/10.3390/fi13050116.
Onojah, A. O., Onojah, A. A., Olumorin, C. O., & Abimbola, I. O. (2020). Study Technology: The Suitable Tenacity to Learning Snags. JPI (Jurnal Pendidikan Indonesia), 9(3), 497–507. https://doi.org/10.23887/jpi-undiksha.v9i3.25191.
Özmen, H. (2008). Determination of students’ alternative conceptions about chemical equilibrium: A review of research and the case of Turkey. Chemistry Education Research and Practice, 9(3), 225–233. https://doi.org/10.1039/b812411f.
Shanks, J. D., Izumi, B., Sun, C., Martin, A., & Shanks, C. B. (2017). Teaching undergraduate students to visualize and communicate Public Health data with infographics. Frontiers in Public Health, 5(NOV), 1–6. https://doi.org/10.3389/fpubh.2017.00315.
Shavelson, R. J., Young, D. B., Ayala, C. C., Brandon, P. R., Furtak, E. M., Ruiz-Primo, M. A., Tomita, M. K., & Yin, Y. (2008). On the impact of curriculum-embedded formative assessment on learning: A collaboration between curriculum and assessment developers. Applied Measurement in Education, 21(4), 295–314. https://doi.org/10.1080/08957340802347647.
Shernoff, D. J., Sinha, S., Bressler, D. M., & Ginsburg, L. (2017). Assessing teacher education and professional development needs for the implementation of integrated approaches to STEM education. International Journal of STEM Education, 4(1), 1–16. https://doi.org/10.1186/s40594-017-0068-1.
Sung, Y. T., Chang, K. E., & Liu, T. C. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers and Education, 94, 252–275. https://doi.org/10.1016/j.compedu.2015.11.008.
Teo, T., & Zhou, M. (2017). The influence of teachers’ conceptions of teaching and learning on their technology acceptance. Interactive Learning Environments, 25(4), 513–527. https://doi.org/10.1080/10494820.2016.1143844.
Vongkulluksn, V. W., Matewos, A. M., Sinatra, G. M., & Marsh, J. A. (2018). Motivational factors in makerspaces: a mixed methods study of elementary school students’ situational interest, self-efficacy, and achievement emotions. International Journal of STEM Education, 5(1). https://doi.org/10.1186/s40594-018-0129-0.
Wolters, C. A., & Benzon, M. B. (2013). Assessing and predicting college students use of strategies for the self-regulation of motivation. Journal of Experimental Education, 81(2), 199–221. https://doi.org/10.1080/00220973.2012.699901.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Tadesse Hagos, Dereje Andargie
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with the Journal of Education Technology agree to the following terms:
- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. (See The Effect of Open Access)