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1. ATE Assessment Practices: Reconceptualizing the Role of Participants in Professional Development Evaluation

   Gullickson, A ; Datta, R ; Chen, M ( March 2024 , Journal of advanced technological education)

   Research shows formative assessments substantially strengthen learning and support summative assessment/evaluation practices. These practices are not widely applied in ATE's professional development (PD) efforts. This study focuses on participant teachers' assessment involvement to increase student learning and enhance outcome evaluations. We surveyed all principal investigators of ATE projects in 2022 who applied assessments in their 2021 PD efforts (N=70). Findings show that a minority of PD efforts apply formative assessment practices to strengthen PD outcomes or meet ATE's evaluation specifications. Assessment practices were most prevalent for summative purposes at the close of PD activity; a large majority assessed teachers' interest and learning in the PD and their intentions to use and teach what was learned on return to their classrooms. A third or less followed up to assess outcomes in teachers' schools. Similarly, thirty percent or less addressed matters of context at any stage of the PD efforts, and a few, 11 percent, followed up to assess the context in the schools. Concomitantly, the findings show where and how attention to formative assessment in the PD learning process can increase teacher involvement in assessment practices, making PD instruction more effective and strengthening outcome evaluations in participant teachers' home classrooms. 

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2. Formative assessment through think alouds

   https://doi.org/10.5951/MTLT.2020.0245  

   Hicks, T ; Bostic, J ( July 2021 , Mathematics teaching and learning)

   Barlow, A. (Ed.)

   We describe how teachers used a formative assessment approach called whole class think alouds, which may happen at any time during everyday instruction and foster evidence-based instructional practices. They allow students to collaborate and orally communicate their problem solving with a goal of assessing to promote learning. 

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3. Improving Automated Evaluation of Formative Assessments with Text Data Augmentation.

   https://doi.org/10.1007/978-3-031-11644-5_32  

   Cochran, K. ( July 2022 , Artificial Intelligence in Education. AIED 2022. Lecture Notes in Computer Science, vol 13355.)

   Rodrigo, M.M. (Ed.)

   Formative assessments are an important component of instruction and pedagogy, as they provide students and teachers with insights on how students are progressing in their learning and problem-solving tasks. Most formative assessments are now coded and graded manually, impeding timely interventions that help students overcome difficulties. Automated evaluation of these assessments can facilitate more effective and timely interventions by teachers, allowing them to dynamically discern individual and class trends that they may otherwise miss. State-of-the-art BERT-based models dominate the NLP landscape but require large amounts of training data to attain sufficient classification accuracy and robustness. Unfortunately, educational data sets are often small and unbalanced, limiting any benefits that BERT-like approaches might provide. In this paper, we examine methods for balancing and augmenting training data consisting of students’ textual answers from formative assessments, then analyze the impacts in order to improve the accuracy of BERT-based automated evaluations. Our empirical studies show that these techniques consistently outperform models trained on unbalanced and unaugmented data. 

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4. Assessment for Learning: Helping Children Build on What They Know

   Baroody, A. J. ; Pellegrino, J. W. ( January 2023 , American Educational Research Association Annual Meeting)

   Wiebe, E. N. ; Harris, C. J. ; Grover, S. (Ed.)

   Efforts to improve instruction frequently focus on fostering meaningful learning—learning based on conceptual understanding—as opposed to knowledge memorized by rote. Consistent with Dewey’s (1963) principle of interaction, fostering meaningful learning entails identifying what children already know and do not know and building on the former to learn (moderately) new knowledge (Claessens & Engel, 2013; Fyfe et al., 2012; Piaget, 1964; Vygotsky, 1978). A learning trajectory (LT) approach to instruction—which includes conceptually and research-based and goals, a research-based learning progression of successive developmental levels, and research-based teaching activities to promote each level—epitomizes such an effort (Clements & Sarama, 2008; Confrey et al., 2012). Formative, classroom-based assessment—ongoing assessment to guide and monitor student learning (Black et al., 2003; Cizek, 2010; Author, 2018a)—is an integral aspect of the LT approach (Daro et al., 2011). In contrast to more commonly used summative assessment strategy (e.g., a unit test given at the end of an instruction unit to assess whether unit content has been mastered and grade progress), formative assessment serves to identify what developmental level a child has already achieved and the next developmentally appropriate level on which instruction should begin (Author, 2018a). Moreover, children are regularly assessed during instruction to gauge whether they–individually or collectively–have mastered a developmental level before instruction proceeds with the next higher level. In sum, “the LT approach involves using formative assessment (National Mathematics Advisory Panel, 2008; Shepard et al., 2018) to provide instructional activities aligned with empirically validated developmental progressions (Fantuzzo, Gadsden, & McDermott, 2011). Although research has shown that LT-based instruction is more efficacious, research is needed to evaluate the add-on value of the formative assessment components of LT-based instruction on student outcomes and the professional development of teachers. This presentation will highlight future lines of research that would provide insight into underlying theory and more productive strategies. Because LTs “need to be supplemented with consideration of obstacles that the student must overcome,” much needs to be learned about the obstacles posed by the content itself, instructional materials, and teachers (Ginsburg, 2009). 

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5. Exploring Middle School Students’ Understanding of Algorithms Using Standards-Aligned Formative Assessments: Teacher and Researcher Perspectives

   https://doi.org/10.22318/icls2023.719736  

   Basu, Satabdi ; Rutstein, Daisy ; Tate, Carol ; Rachmatullah, Arif ; Yang, Hui ; Ortiz, Christopher ( October 2023 , International Society of the Learning Sciences)

   ‘Algorithms’ is a core CS concept included in the K-12 CS standards, yet student challenges with understanding different aspects of algorithms are still not well documented, especially for younger students. This paper describes an approach to decompose the broad middle-school ‘algorithms’ standard into finer grained learning targets, develop formative assessment tasks aligned with the learning targets, and use the tasks to explore student understanding of, and challenges with, the various aspects of the standard. We present a number of student challenges revealed by our analysis of student responses to a set of standards-aligned formative assessment tasks and discuss how teachers and researchers interpreted student responses differently, even when using the same rubrics. Our study underscores the importance of carefully designed standards-aligned formative assessment tasks for monitoring student progress and demonstrates the need for teacher content knowledge to effectively use formative assessments during CS instruction. 

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