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Secil Caskurlu; Yasin Yalçin; Jaesung Hur; Hui Shi; James D. Klein – TechTrends: Linking Research and Practice to Improve Learning, 2025
This exploratory qualitative study examined how instructional designers use data to make decisions during the instructional design process. Participants included full-time instructional designers (n = 9) who were involved in one or more phases of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) across different job sectors,…
Descriptors: Data Use, Instructional Design, Decision Making, Data Collection
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Atezaz Ahmad; Jan Schneider; Dai Griffiths; Daniel Biedermann; Daniel Schiffner; Wolfgang Greller; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over-emphasis on data-driven approaches at the expense of paying attention to learning designs. Method and objective: In response to this critique, we investigated the role of learning design in learning analytics through a…
Descriptors: Instructional Design, Learning Analytics, Data Use, Literature Reviews
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Hiroaki Ogata; Changhao Liang; Yuko Toyokawa; Chia-Yu Hsu; Kohei Nakamura; Taisei Yamauchi; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Izumi Horikoshi; Rwitajit Majumdar – Technology, Knowledge and Learning, 2024
This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from…
Descriptors: Educational Technology, Instructional Design, Cooperation, Data Use
Schoepp, Rosemarie – ProQuest LLC, 2023
Data-driven decision making (DDDM) is an important teaching practice that can positively influence student achievement by using assessment data to make instructional decisions. The problem is that teachers do not always use this practice. Teachers' perspectives of DDDM can influence their data use practices. This basic qualitative study was…
Descriptors: Teacher Attitudes, Data Use, Instructional Design, Decision Making
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Taub, Michelle; Azevedo, Roger – New Directions for Teaching and Learning, 2023
The goal of this chapter is to propose a cyclical process of how teachers can use multimodal multichannel data of cognitive, affective, metacognitive, motivational, and social processes to assist with the understanding of their own and their students' self-regulated learning (SRL), and their subsequent instructional decision making. What…
Descriptors: Independent Study, Learning Processes, Instructional Design, Decision Making
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Qian Liu; Tehmina Gladman; Julia Muir; Chen Wang; Rebecca Grainger – SAGE Open, 2023
One apparent challenge associated with learning analytics (LA) has been to promote adoption by university educators. Researchers suggest that a visualization dashboard could serve to help educators use LA to improve learning design (LD) practice. We therefore used an educational design approach to develop a pedagogically useful and easy-to-use LA…
Descriptors: Learning Management Systems, Learning Analytics, Visual Aids, Instructional Design
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Chih-Hsiung Tu; Patricia Peterson; Cherng-Jyh Yen; Hoda Harati; Catharyn Shelton; Laura Sujo-Montes – Educational Media International, 2023
COVID-19 has emphasized the importance of holistic education with fostering stu- dents' multiple intelligences through effective social and emotional learning (SEL). Understanding students' SEL not only supports students' learning performance, it's also beneficial to inform teachers to provide more adequate social-communicative, metacognitive, and…
Descriptors: Data Use, Diaries, Electronic Learning, Social Emotional Learning
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Tamra Ross; Rachel Sondergaard; Cindy Ives; Andrew Han; Sabine Graf – Technology, Knowledge and Learning, 2025
To meet student demand for responsive, adaptable, and up-to-date online courses, educators and learning designers need tools to analyse student interactions with their peers, educators and learning resources. Learning Management Systems (LMSs) store large volumes of detailed user data, but offer only limited, pre-set reports and visualizations to…
Descriptors: Access to Information, Learning Analytics, Instructional Design, Evaluation Methods
Ednah Nwafor; Olivia Kelly; Ally Skoog-Hoffman; Faye Kroshinsky – Collaborative for Academic, Social, and Emotional Learning, 2023
This brief shares learnings from Building Equitable Learning Environments (BELE) district partnerships around the sixth Essential Action: Measure What Matters. This Essential Action focuses on achieving equitable learning environments through the routine collection and review of relevant student feedback data to co-design new practices and…
Descriptors: Middle School Students, High School Students, Student Experience, Student Attitudes
Center on Positive Behavioral Interventions and Supports, 2022
This practice guide is an updated version of "Supporting and Responding to Behavior: Evidence-based Classroom Strategies for Teachers" (see ED619696) that replaces, rather than supplements, the first version. This guide summarizes evidence-based, positive, and proactive practices that support and respond to students' social, emotional,…
Descriptors: Evidence Based Practice, Student Behavior, Intervention, Classroom Techniques