A Review of Tools and Techniques for Data-Enabled Formative Assessment

Abstract

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose of formative assessment. We identified two categories of data: machine-graded and activity stream data. The data were processed using three methods: unprocessed activity streams, descriptive data analysis, and data mining. Processed data were presented to students through reports and real-time feedback and to instructors through reports and visual dashboards.

A Survey of Current Machine Learning Approaches to Student Free-Text Evaluation for Intelligent Tutoring

“…Alongside conversational ITS, a large amount of work centres on educational tools that automatically evaluate students' work on different subjects and provide hints or feedback with respect to a specific task (Deeva et al, 2021;Nyland, 2018). In the absence of the dialog management task, the automatic evaluation of students' work forms the central technological challenge for these tools.…”

Examining Technologies Used in K-12 School Districts: A Proposed Framework for Classifying Educational Technologies

“…Although the educational technologies represented in our STC framework are well represented in both research and practice, findings from this study highlight the range of technologies used in K-12 schools that fall outside of this category. A better understanding of the technologies that fall within this category can also help better understand the data collected from these technologies that can be harnessed through data analytics to inform decision-making in K-12 schools (Bowers, 2021; Nyland, 2018).…”

“…I have some support, but I don't have as much pull as a larger school district. And the time to really dedicate to getting [new technologies] set up is really hard for me.” Additionally, technology personnel who have expertise in data analytics can support educators and administrators to maximize the potential of the data collected by educational technologies to improve learning outcomes (Nyland, 2018). Having the STC framework as a tool to represent the range of technology expertise needed can support technology personnel in advocating for the specialized training needed to effectively fulfill K-12 technology needs.…”

“…With increased technology, the use in K-12 schools also comes a wealth of data that is collected and stored about each of the system's users, including students. Although there are some concerns about data privacy associated with the wealth of data collected by educational technology (Schlosser et al, 2022), when harnessed appropriately, data analytics can provide students, educators, and parents with a wealth of useful information (Baker, 2021; Bowers, 2021; Nyland, 2018). Data processing methods can provide teachers and students with valuable formative assessment data based on student activity and performance that can guide future instruction (Nyland, 2018).…”

“…Although there are some concerns about data privacy associated with the wealth of data collected by educational technology (Schlosser et al, 2022), when harnessed appropriately, data analytics can provide students, educators, and parents with a wealth of useful information (Baker, 2021; Bowers, 2021; Nyland, 2018). Data processing methods can provide teachers and students with valuable formative assessment data based on student activity and performance that can guide future instruction (Nyland, 2018). According to Bowers (2021), data analytics can identify patterns in student data to provide early warning predictors of students’ risk of dropping out of school.…”