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Soyoung Park; Pamela M. Stecker; Sarah R. Powell – Intervention in School and Clinic, 2024
This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…
Descriptors: Student Evaluation, Individualized Instruction, Mathematics Instruction, Progress Monitoring
Švábenský, Valdemar; Vykopal, Jan; Celeda, Pavel; Tkácik, Kristián; Popovic, Daniel – Education and Information Technologies, 2022
Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs in an interactive learning environment that enables completing sophisticated tasks in full-fledged operating systems, networks, and applications. During the training, the learning environment allows…
Descriptors: Computer Security, Information Security, Training, Data Collection
Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
Clavié, Benjamin; Gal, Kobi – International Educational Data Mining Society, 2020
We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…
Descriptors: Student Behavior, Electronic Learning, Metadata, Prediction
Fawcett, Darcy – set: Research Information for Teachers, 2019
This Assessment News article introduces readers to a statistical approach to making sense of student assessment data in order to help teachers understand whether or not changes in practice have made a difference to learning. It Worked! is the brainchild of Darcy Fawcett, HoD Science at Gisborne Boys' High School, and Across-School Teacher for the…
Descriptors: Data Analysis, Data Use, Evidence Based Practice, Communities of Practice
NWEA, 2018
When Superintendent Curtis Craig, Ed.S., came to the Rensselaer Central Schools Corporation in 2015, he discovered an assessment problem common to many districts. The assessment results--Renaissance STAR and Acuity at the time--were not well aligned to the new, more rigorous standards the district and state had recently adopted. In addition, some…
Descriptors: Alignment (Education), Student Evaluation, Academic Standards, School Districts
Guenter, Cris – National Art Education Association, 2019
The teaching performance expectations and assignments that preservice art teachers currently address in field experiences and in their coursework are designed to help them meet the expectations of being a quality art educator in the 21st century. These assignments may be very different from the assignments that art educators had in their…
Descriptors: Data Use, Decision Making, Data Collection, Art Education
Smith, Elizabeth E.; Gordon, Sarah – Research & Practice in Assessment, 2019
Although faculty are an important part of collecting, analyzing, and using student learning data for improvement, significant barriers often prevent faculty from being involved in assessment work outside the classroom. One potential obstacle to faculty involvement in assessment is the misalignment between the work and faculty rewards structures.…
Descriptors: Rewards, College Faculty, Student Evaluation, Teacher Attitudes
Fischer, Christian; Pardos, Zachary A.; Baker, Ryan Shaun; Williams, Joseph Jay; Smyth, Padhraic; Yu, Renzhe; Slater, Stefan; Baker, Rachel; Warschauer, Mark – Review of Research in Education, 2020
The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with…
Descriptors: Data Analysis, Data Collection, Decision Making, Instructional Effectiveness
Bhattacharya, Madhumita; Coombs, Steven – Journal of Interactive Learning Research, 2018
This paper explores the usefulness of formalytics for sustainable learning improvement linked to lifelong learning. This can be achieved in two ways; firstly, by providing students with automatic VLE generated feedback of information giving an analysis of their personal data gathered on their learning engagement and performance; secondly, by…
Descriptors: Feedback (Response), Sustainability, Lifelong Learning, Educational Research
Selwyn, Neil – British Journal of Sociology of Education, 2018
This article reviews two recent books on the rising use of digital data in schools and university education, reflecting on areas of further research, analysis, and action. The books discussed are: (1) "The datafication of primary and early years education: playing with numbers," by A. Bradbury and G. Roberts-Holmes, London, Routledge,…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
Sandlin, Michele – College and University, 2019
This feature focuses on the five areas an institution needs to know before implementing holistic measures. These include: what does a holistic review entail, how to be legally complaint, Sedlacek's noncognitive variables, applying student success measures, and the vital importance of training.
Descriptors: Predictor Variables, Success, Holistic Approach, Compliance (Legal)
Beck, Jori S.; Morgan, Joseph John; Brown, Nancy; Whitesides, Heather; Riddle, Derek R. – Educational Forum, 2020
The current study explored preservice and inservice teachers' perspectives on data literacy for teaching. Semi-structured interviews were employed with 12 teacher candidates in elementary and special education. The findings revealed participants' misconceptions regarding formative and summative data; their understanding of the value of formative…
Descriptors: Preservice Teachers, Literacy, Preservice Teacher Education, Undergraduate Students
Valenza, Marco; Dreesen, Thomas; Kan, Sophia – UNICEF Office of Research - Innocenti, 2022
One tool that many families own, across the globe, is a basic mobile phone. The use of low-cost basic mobile phones for educational purposes in humanitarian settings is critical where access to connectivity and higher cost devices is limited. The portability of mobile phones, combined with their communication features, offers multiple uses to…
Descriptors: COVID-19, Pandemics, Telecommunications, Handheld Devices
Center on Standards and Assessments Implementation, 2018
The recommendations in this brief create a framework for using data effectively to make instructional decisions. The availability of student-level data for educators has pushed forward the movement to strengthen the role of data to guide instruction and improve student learning. While improvements in technology and assessments, as well as recent…
Descriptors: Student Evaluation, Information Utilization, Data Collection, Data Analysis