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Jennings, Austin S. – Elementary School Journal, 2023
Teachers' data literacy and interpretive process are critical to understanding how they make sense of data. However, little is known about how mental representations shape and evolve in response to teachers' interpretive process. In the present study, I model and explore this recursive relationship between teachers' cognitive framing and…
Descriptors: Data Interpretation, Cognitive Processes, Academic Achievement, Student Evaluation
Groth, Randall E.; Choi, Yoojin – Educational Studies in Mathematics, 2023
Learning to interpret data in context is an important educational outcome. To assess students' attainment of this outcome, it is necessary to examine the interplay between their contextual and statistical reasoning. We describe a research method designed to do so. The method draws upon Toulmin's (1958, 2003) model of argumentation for the first…
Descriptors: Student Evaluation, Data Interpretation, Evaluative Thinking, Evaluation Methods
Wang, Karen D.; Cock, Jade Maï; Käser, Tanja; Bumbacher, Engin – British Journal of Educational Technology, 2023
Technology-based, open-ended learning environments (OELEs) can capture detailed information of students' interactions as they work through a task or solve a problem embedded in the environment. This information, in the form of log data, has the potential to provide important insights about the practices adopted by students for scientific inquiry…
Descriptors: Data Use, Educational Environment, Science Process Skills, Inquiry
Wang, Fei; Huang, Zhenya; Liu, Qi; Chen, Enhong; Yin, Yu; Ma, Jianhui; Wang, Shijin – IEEE Transactions on Learning Technologies, 2023
To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…
Descriptors: Cognitive Measurement, Diagnostic Tests, Models, Prediction
A. Corinne Huggins-Manley; Jing Huang; Jerri-ann Danso; Wei Li; Walter L. Leite – Journal of Experimental Education, 2024
The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…
Descriptors: Student Evaluation, Educational Environment, Educational Change, COVID-19
Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
Márió Tibor Nagy; Erzsébet Korom – Journal of Baltic Science Education, 2023
Nowadays, the assessment of student performance has become increasingly technology-based, a trend that can also be observed in the evaluation of scientific reasoning, with more and more of the formerly paper-based assessment tools moving into the digital space. The study aimed to examine the reliability and validity of the paper-based and…
Descriptors: Science Process Skills, Elementary School Students, Grade 4, Science Tests
A. Corinne Huggins-Manley; Jing Huang; Jerri-ann Danso; Wei Li; Walter L. Leite – Grantee Submission, 2023
The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…
Descriptors: Student Evaluation, Educational Environment, Educational Change, COVID-19
Burkholder, Eric; Walsh, Cole; Holmes, N. G. – Physical Review Physics Education Research, 2020
Physics education research (PER) has long used concept inventories to investigate student learning over time and to compare performance across various student subpopulations. PER has traditionally used normalized gain to explore these questions but has begun to use established methods from other fields, including Cohen's "d," multiple…
Descriptors: Physics, Science Education, Educational Research, Science Tests
Brown, Stephanie T.; McGreevy, Jeanette; Berigan, Nick – New Directions for Teaching and Learning, 2018
This chapter describes how any campus can use collaborative professional integration and three "data buckets" (pre-college, during-college, and post-college buckets) to disaggregate assessment evidence, interpret findings contextually, and focus attention on realistic actions to improve student performance in the areas of leverage over…
Descriptors: College Students, Academic Achievement, Data, Student Evaluation
Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Lazarus, Sheryl S.; Hinkle, Andrew R.; Liu, Kristin K.; Thurlow, Martha L.; Ressa, Virginia A. – National Center on Educational Outcomes, 2021
The National Center on Educational Outcomes (NCEO) held a virtual meeting of an Interim Assessment Advisory Panel on February 16 and 17, 2021, to tap into the panel members' collective knowledge about using interim assessments to support valid interpretations of what students with disabilities know and can do. The panel represented…
Descriptors: Student Evaluation, Students with Disabilities, Guidance, State Departments of Education
Whitaker, Douglas; Jacobbe, Tim – Journal of Statistics Education, 2017
Bar graphs and histograms are core statistical tools that are widely used in statistical practice and commonly taught in classrooms. Despite their importance and the instructional time devoted to them, many students demonstrate misunderstandings when asked to read and interpret bar graphs and histograms. Much of the research that has been…
Descriptors: Secondary School Students, Graphs, Knowledge Level, Statistics
Education Scotland, 2020
Through our national thematic reports HM Inspectors of Education share their professional view on particular aspects of education. This report focuses on sharing the key features which, when taken together, make the greatest difference to using assessment effectively to improve learning and teaching and in turn, outcomes for children and young…
Descriptors: Foreign Countries, Educational Assessment, General Education, Educational Practices