M.Ed on Education and Innovation: EDUS3 - Effective Assessment in Science Education

This course equips participants with the knowledge and skills to apply theory- and research-informed approaches to formative and summative assessment in science education. It emphasizes inclusive, culturally responsive practices grounded in Emirati values, character, and culture, and considers how science assessment can support learning, and prepare learners for a changing world. In line with the National Educators’ Competency Framework, the course supports students build effective science assessment practices and cultural sensitivity. Participants will explore practical strategies for clarifying learning objectives, providing feedback, engaging students in peer and self-assessment, and using assessment data to inform improvements in science teaching and learning. Students will also build competence in the design of valid, reliable and fair summative tests of students’ learning. Ethical and effective integration of AI tools for enhancing science assessment is an explicit focus of the course. Through hands-on tasks, critical reflection, and evidence-based evaluation, participants will build professional competence in creating effective, meaningful, and future-ready assessment practices that align with contemporary educational standards and meet the needs of all learners.

Week 1

Course Overview

• Clarifying learning objectives and success criteria
• Defining meaningful learning goals in science classrooms
• Linking success criteria to student understanding

Required Reading

• Abell, S.K., Siegel, M.A. (2011). Assessment Literacy: What Science Teachers Need to Know and Be Able to Do. In: Corrigan, D., Dillon, J., Gunstone, R. (eds) The Professional Knowledge Base of Science Teaching. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3927-9_12
• Furtak, E. M., & Ruiz-Primo, M. A. (2008). Making students’ thinking explicit in writing and discussion: An analysis of formative assessment prompts. Science Education, 92(5), 799–824. https://doi.org/10.1002/sce.20270

Recommended Reading:

• Harlen, W. (2013). Assessment & inquiry-based science education. Issues in Policy and Practice. Published by the Global Network of Science Academies (IAP) Science Education Programme (SEP).

Week 2

• Designing formative assessment strategies
• Crafting science-specific questioning and feedback practices
• Embedding formative assessment strategies within inquiry-based science lessons

Required Reading:

• Ruiz-Primo, M. A., & Furtak, E. M. (2007). Exploring teachers’ informal formative assessment practices and students’ understanding in the context of scientific inquiry. Journal of Research in Science Teaching, 44(1), 57–84. https://doi.org/10.1002/tea.20163
• Black, P., & Harrison, C. (2001). Feedback in questioning and marking: The science teacher's role in formative assessment. School Science Review, 82(301), 55–61.

Recommended Reading:

• Coffey, J. E., Hammer, D., Levin, D. M., & Grant, T. (2011). The missing disciplinary substance of formative assessment. Journal of Research in Science Teaching, 48(10), 1109–1136. https://doi.org/10.1002/tea.20440

Week 3

• Applying formative assessment strategies in practice
• Using student explanations as evidence for learning
• Adapting teaching strategies based on formative assessment data

Required Reading:

• Furtak, E. M., Morrison, D., & Kroog, H. (2014). Investigating the Link Between Learning Progressions and Classroom Assessment. Science Education, 98(4), 640–673. https://doi.org/10.1002/sce.21122
• Recommended Reading:
• Aydeniz, M., & Southerland, S. A. (2012). A national survey of middle and high school science teachers’ responses to standardized testing. Journal of Science Teacher Education, 23(5), 367–393. https://doi.org/10.1007/s10972-012-9266-3

Week 4

• Peer and self-assessment strategies
• Facilitating student-led dialogue and critique

Required Reading:

• Dutta, S., He, M., & Tsang, D. C. W. (2023). Reflection and peer assessment to promote self-directed learning in higher education. Journal of Educational Research and Reviews, 11(3), 35–46. https://doi.org/10.33495/jerr_v11i3.23.111

Week 5

• Using AI tools in formative assessment
• Exploring AI’s role in visualizing science concepts
• Leveraging learning analytics for real-time feedback

Required Reading:

• Zhai, X., & Nehm, R. H. (2023). AI and formative assessment: The train has left the station. Journal of Research in Science Teaching, 60(6), 1390–1398. https://doi.org/10.1002/tea.21885
• Zhai, X., Zhang, M., & Li, M. (2020). Using machine learning and learning analytics to investigate the impact of prior knowledge on students’ learning. Journal of Science Education and Technology, 29(3), 321–333. https://doi.org/10.1007/s10956-020-09823-8

Week 6

• Designing valid, reliable summative assessments
• Ensuring fair and unbiased science assessments
• Using measurement models to strengthen assessment quality

Required Reading:

• Pellegrino, J. W., Wilson, M. R., Koenig, J. A., Beatty, A. S., National Research Council (U.S.). Center For Education. Board On Testing And Assessment, National Research Council (U.S.). Board On Science Education, & National Research Council (U.S.).Division Of Behavioral And Social Sciences And Education. (2014). Developing assessments for the Next Generation Science Standards. The National Academies Press.
• Hsu, TC., Chang, YS., Chen, MS. et al. (2022). A validity and reliability study of the formative model for the indicators of STEAM education creations. Educ Inf Technol 28, 8855–8878 (2023). https://doi.org/10.1007/s10639-022-11412-x

Week 7

• Aligning assessments with learning objectives and curriculum
• Mapping science assessments to curriculum frameworks

Required Reading:

• Zhao, L., Zhao, B. & Li, C. (2023). Alignment analysis of teaching–learning-assessment within the classroom: how teachers implement project-based learning under the curriculum standards. Discip Interdscip Sci Educ Res 5, 13 (2023). https://doi.org/10.1186/s43031-023-00078-1
• Cobern, W. W., Schuster, D., Adams, B., Skjold, B. A., Muğaloğlu, E. Z., Bentz, A., & Sparks, K. (2014). Pedagogy of Science Teaching Tests: Formative assessments of science teaching orientations. International Journal of Science Education, 36(13), 2265–2288. https://doi.org/10.1080/09500693.2014.918672

Assignment 1 due
Assignment 2 Introduced and explained

Week 8

• Using summative data to inform and improve teaching and learning
• Translating test results into actionable teaching steps
• Creating improvement plans based on science assessment data

Required Reading:

• Black, P., & Wiliam, D. (2018). Classroom assessment and pedagogy. Assessment in Education: Principles, Policy & Practice, 25(6), 551–575. https://doi.org/10.1080/0969594X.2018.1441807
• Ruiz-Primo, M. A., & Furtak, E. M. (2006). Informal formative assessment and scientific inquiry: Exploring teachers’ practices and student learning. Educational Assessment, 11(3–4), 205–235. https://doi.org/10.1207/s15326977ea1103&4_4
• Haines, B. (2007). Cognitive-Affective Learning Bibliography (Revised 2007). Journal of Cognitive Affective Learning, 4(1), 32-80.

Week 9

• Cultural responsiveness in assessment
• Integrating Emirati values and cultural awareness in science assessment
• Designing inclusive assessments for diverse learners, aligned with the National Educators’ Competency Framework

Required Reading:

• Lee, O. (2005). Science education with English language learners: Synthesis and research agenda. Review of Educational Research, 75(4), 491–530. https://doi.org/10.3102/00346543075004491
• Buxton, C. A., & Lee, O. (2014). English learners in science education. In Handbook of research on science education, volume II (pp. 204-222). Routledge

Week 10

• Ethical considerations and AI in assessment
• Addressing ethical risks of AI-driven assessment tools
• Balancing automation with human judgment in science assessments

Required Reading:

• Bulut, O., Beiting-Parrish, M., Casabianca, J. M., Slater, S. C., Jiao, H., Song, D., Ormerod, C. M., Fabiyi, D. G., Ivan, R., Walsh, C., Rios, O., Wilson, J., Yildirim-Erbasli, Seyma N, Wongvorachan, T., Liu, J. X., Tan, B., & Morilova, P. (2024). The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.2406.18900

Week 11

Course summary

• The power of feedback in formative assessments
• Summative assessments.

Required Reading:

• Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487

Assessment 2 students presentations

Assessment 2 due