In this research, we use a process data analysis approach to gather additional evidence about students' argumentation skills beyond their performance scores in a computer-based assessment. This game-enhanced scenario-based assessment (named Seaball) included five activities that require students to demonstrate their argumentation skills within a…

This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…

IEA's International Computer and Information Literacy Study (ICILS) 2018 is designed to assess how well students are prepared for study, work, and life in a digital world. The study measures international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and…

Computer-based assessments allow practitioners to collect rich process data by logging students' interactions with assessment tasks. In addition to providing final responses to test questions, computer-based assessments promise to furnish more evidence to support claims about what a student knows and can do through logging process data in log…

Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses ("product data"), students' log files offer additional…

This paper reports on a design-based implementation study of the use of a diagnostic classroom assessment tool framed on learning trajectories (LTs) for middle grades mathematics, where teachers and students are provided immediate data on students' progress along LTs. The study answers the question: "How can one characterize the challenges…

IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…

In this chapter, we provide an overview of the design, data-collection, and data-analysis efforts for a digital learning and assessment environment for scientific inquiry / science practices called "Inq-ITS" ("I"nquiry "I"ntelligent "T"utoring "S"ystem; www.inqits.org). We first present a brief…

This paper presents a novel examination of the impact of students' feedback choices and performance on their feedback memory. An empirical study was designed to collect the choices to seek critical feedback from a hundred and six Grade 8 middle-school students via Posterlet, a digital assessment game in which students design posters. Upon…

This paper briefly discusses four measurement challenges of data science or "big data" in educational assessments that are enabled by technology: 1. Dealing with change over time via time-based data. 2. How a digital performance space's relationships interact with learner actions, communications and products. 3. How layers of…

There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…

We present "Science Assistments," an interactive environment, which assesses students' inquiry skills as they engage in inquiry using science microworlds. We frame our variables, tasks, assessments, and methods of analyzing data in terms of "evidence-centered design." Specifically, we focus on the "student model," the…

The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…

Motivation in distance education (DE) has been studied mostly at the postsecondary level with few studies having been conducted at the high-school level. This paper breaks with this tradition by reporting on the perspectives on motivation of 42 Canadian high-school DE teachers. Data collection involved one-hour long, semi-structured telephone…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…