The investigation examined the consequences of design-based learning integrated with the educational neuroscience instructional model (DEN) and conventional instructional model (CIM) for tenth-grade students’ learning outcomes, executive function, and learning stress. Since the physics curriculum is planned to prepare students for discovering complex scientific concepts through real-life experience, the use of the DEN model is necessary to measure its efficiency. The cluster random sampling method was used to select 63 out of 494 tenth-grade students from Numsomphittayakhon School, Thailand. The researcher administered seven tests and employed the pre-test and post-test control group research design. The experimental and control groups were taught using DEN and CIM, respectively. The data were analyzed by repeated measures of multivariate analysis of variance to study the consequences of both instructional models. The results indicated that students from both groups seemed to demonstrate no significant difference in all the pre-tests on the dependent variables before the treatment with the instructional models. However, MANOVA analysis discovered that the experimental group’s physics learning outcomes and executive functions were better than the control group. Moreover, students from the experimental group seemed to have a lower learning stress level than those from the control group. The results have successfully contributed to contemporary awareness of the efficiency of the DEN model to promote student learning outcomes and executive functions and reduce students’ learning stress.

• Anderson, O. R. (2009). Neurocognitive theory and constructivism in science education: A review of neurobiological, cognitive and cultural perspectives. Brunei International Journal of Science & Mathematics Education, 1(1), 1-32.

• Bunterm, T., Ketchatturat, J., Samranjai, J., Methaneethorn, J., Wattanathorn, J., Muchimapura, S., Wannanon, P., Uopasai, S., Srikoon, S., & Werachairatana, S. (2015). The development of cognitive function battery test: Thai version. National Research Council of Thailand.

• Bellini, J. L., & Rumrill, P. D. (2009). Research in rehabilitation counseling: A guide to design, methodology, and utilization (2nd ed.). Charles Thomas.

• Chinnery, A. (2014). Teaching concept and model. In Encyclopedia of educational theory and philosophy (pp. 792-796). SAGE Publications, Inc. https://doi.org/10.4135/9781483346229

• Chiou, G. L., Lee, M. H., & Tsai, C. C. (2013). High school students’ approaches to learning Physics with relationship to epistemic views on Physics and conceptions of learning Physics. Research in Science & Technological Education, 31(1), 1-15. https://doi.org/10.1080/02635143.2013.794134

• Cobb, P., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9-13.

• Cohen, I., Berkov, T., & Gilboa, G. (2021). Total-variation mode decomposition. https://guygiboa.net.technion.ac.il/files/2021/05/ssvm_Cohen_Berkov_Gilboa.pdf

• Diamond, A. D. (2013). Executive functions. Annual Review of Psychology, 64, 135-168. https://doi.org/10.1146/annurev-psych-113011-143750

• Engel, A. K., Senkowski, D., & Schneider, T. R. (2012). Multisensory integration through neural coherence. In M. M. Murray & M. T. Wallace (Eds.), The neural bases of multisensory processes. CRC Press/Taylor & Francis.

• Everitt, B. S., & Dunn, G. (1991). Applied multivariate data analysis (2nd ed.). Edward Arnold.

• Gilbert, S., & Burgess, P. (2008). Executive function. Current Biology, 18(3), R110-R114.

• Goswami, U. (2008). Cognitive development: The learning brain. Psychology Press.

• Hair, J. F., Back, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). Pearson.

• Institute for the Promotion of Teaching Science and Technology. (2012). Science measurement and assessment. V. Print.

• Isman, A. (2011). Instructional design in education: New model. The Turkish Online Journal of Educational Technology, 10(1), 136-142.

• Jacob, C., & Silvanto, J. (2015). How is working memory content consciously experienced? The ‘conscious copy’ model of WM introspection. Neuroscience and Biobehavioral Reviews, 55, 510-519. https://doi.org/10.1016/j.neubiorev.2015.06.003

• Jordan, R. C., Ruibal-Villasenor, M., Hmelo-silver, C. E., & Etkina, E. (2011). Laboratory materials: Affordances or constraints. Journal of Research in Science Teaching, 48(9), 1010-1025.

• Meltzer, L. (2010). Promoting executive function in the classroom. The Guilford Press.

• Noesselt, T., Bergmann, D., Heinze, H. J., Münte, T., & Spence, C. (2012). Coding of multisensory temporal patterns in human superior temporal sulcus. Frontiers in Integrative Neuroscience, 6(1), 64-78.

• Sanchez-Torres, A. M., Elosua, M. R., Lorente-Omenaca, R., Moreno-Izco, L., & Cuesta, M. J. (2015). A comparative study of the working memory multicomponent model in psychosis and healthy control. Comprehensive Psychiatry, 61, 97-105.

• Sekaran, U. (2003). Research methods for business: A skill building approach (4th ed.). John Wiley and Sons.

• Spalding, K. N., Jones, S. H., Duff, M. C., Tranel, D., & Warren, D. E. (2015). Investigating the neural correlates of schemas: Ventromedial prefrontal cortex is necessary for normal schematic influence on memory. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 35(47), 15746-15751.

• Srikoon, S., Bunterm, T., Nethanomsak, T., & Tang, K. N. (2017). A comparative study of the effects of the neurocognitive-based model and the conventional model of learner attention, working memory and mood. Malaysian Journal of Learning and Instruction, 14(1), 83-110.

• Srikoon, S., Bunterm, T., Nethanomsak, T., & Tang, K. N. (2018). Effects of 5P model on academic achievement, creative thinking, and research characteristics. Kasetsart Journal of Social Sciences, 39(3), 488-495.

• Sripongwiwat, S., Bunterm, T., Srisawat, N., & Tang, K. N. (2016). The construction and neurocognitive-based teaching model for promoting science learning outcomes and creative thinking. Asia Pacific Forum on Science Learning and Teaching, 17(2), 9.

• Sripongwiwat, S., Bunterm, T., & Tang, K. N. (2018). An investigation of learning stressors among secondary school students: A case study in northeast Thailand. Kasetsart Journal of Social Sciences, 39, 197-206. https://doi.org/10.1016/j.kjss.2017.06.002

• Tornee, N. (2014). Development of chemistry teaching model based on constructivism and educational neuroscience for optimizing cognitive ability, problem-solving, and innovation development ability [Unpublished Doctoral dissertation]. Khon Kaen University.

• Tornee, N., Bunterm, T., & Tang, K. N. (2017a). The impacts of inquiry-based learning model on teaching science subject: A case study in Thailand. Turkish Online Journal of Educational Technology, (Special Issue for INTE), 395-402.

• Tornee, N., Bunterm, T., Muchimapura, S., & Tang, K. N. (2017b). The neurocognitive constructivist guided-inquiry based teaching model for promoting attention abilities. Turkish Online Journal of Educational Technology, (Special Issue for INTE), 475-483.

• Uopasai, S., Bunterm, T., Muchimapura, S., & Tang, K. N. (2017). The effect of working memory training on the behavioral, electrophysiological and achievement change. Turkish Online Journal of Educational Technology, (Special Issue for INTE), 331-339.

• Uopasai, S., Bunterm, T., Muchimapura, S., & Tang, K. N. (2018). The effect of constructivism, metacognitive and neurocognitive-based teaching model to enhance veterinary medicine students’ learning outcomes. Pertanika Journal of Social Sciences & Humanities, 26(4), 2313-2331.

• Vaninsky, A. (2017). Educational neuroscience, educational psychology, and classroom pedagogy as a system. American Journal of Educational Research, 5(4), 384-391. https://doi.org/10.12691/education-5-4-6

• Vogel, S., & Schwabe, L. (2016). Learning and memory under stress: Implications for the classroom. NRJ Science of Learning, 1, (16011), 1-10. https://doi.org/10.1038/npjscilearn.2016.11

• Wilkin, C. L. (2014). Enhancing the AIS curriculum: Integration of a research-led, problem-based learning task. Journal of Accounting Education, 32(2), 185-199. https://doi.org/10.1016/j.jaccedu.2014.04.001

• Yang, H. Y., & Chang, C. C. (2015). The effect of attention cueing on science text learning. Tech Know Learn, 23, 357. https://doi.org/10.1007/s10758-015-9264-6

• Yuenyong, C., & Narjaikaew, P. (2009). Scientific literacy and Thailand science education. International Journal of Environmental & Science Education, 4(3), 335-349.

• Yusoff, M. S. B. (2011). The validity and reliability of secondary school stressor questionnaire (3SQ) in identifying stressor among adolescents in secondary school. International Medical Journal, 18(2), 99-105.

• Yusoff, M. S. B. (2016, August 10). The medical student stressor questionnaire: A valid screening tool to discover sources of stress of medical students (Paper presentation). The Innovative Practices in Higher Education Expo 2016 (I-PHES), Kuala Lumpur, Malaysia.