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Leonidas Sakalauskas; Vytautas Dulskis; Darius Plikynas – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Dynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in many applications by a single time series. In this context, however, the methods currently available either lack estimation quality or are…
Descriptors: Structural Equation Models, Time Management, Predictive Measurement, Data Collection
Carla Quinci – Interpreter and Translator Trainer, 2024
This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…
Descriptors: Artificial Intelligence, Translation, Data Collection, Information Retrieval
Voss, Nathaniel M.; Vangsness, Lisa – Educational Measurement: Issues and Practice, 2020
While it is easy to assume that university students who wait until the last minute to complete surveys for their class research requirements provide low-quality data, this issue has not been empirically examined. The goal of the present study was to examine the relation between student research procrastination and two important data quality…
Descriptors: Time Management, College Students, Data Collection, Student Surveys
Maya Murad; KC Collins – Canadian Journal of Learning and Technology, 2024
Procrastination is a prevalent issue among university students and leads to long-term negative impacts on academic performance as well as mental health and quality of life. This paper investigated StudyTracker, a self-tracking digital application (app) that we developed for university students to use to track their study sessions. The app provided…
Descriptors: Computer Oriented Programs, Attention, Self Management, Data Collection
Jo Lein; Jennifer Gripado – Learning Professional, 2024
There are many valuable sources of evaluation data, including -- but not limited to -- professional learning participants. In the authors' work on leadership development and organizational learning for Tulsa Public Schools in Oklahoma, they regularly ask educators to share feedback and perceptions of usefulness of their professional learning. The…
Descriptors: Participant Satisfaction, Surveys, Test Items, Feedback (Response)
Bekir Duz – ProQuest LLC, 2023
This action research study investigates the role of Data-Based Decision-Making (DBDM) in increasing academic outcomes within a charter school network. During Cycle 1, interviews and focus groups with teachers, interventionists, and school deans shed light on critical themes, including leadership, data collection, analytic capacity, and a culture…
Descriptors: Data Use, Decision Making, Outcomes of Education, Educational Improvement
Kocak, Omer; Goktas, Yuksel – International Journal of Contemporary Educational Research, 2021
Smartphones, which enable us to be online everywhere and every time, are also commonly used by students today. This study aims to reveal undergraduate students' habits of using smartphones. With this purpose, the phone usage track application was installed on students' smartphones, and their 7-day use was recorded with the application and was then…
Descriptors: Telecommunications, Handheld Devices, Habit Formation, Computer Use
Jansen, Renée S.; van Leeuwen, Anouschka; Janssen, Jeroen; Kester, Liesbeth – Frontline Learning Research, 2020
To be successful in online education, learners should be able to self-regulate their learning due to the autonomy offered to them. Accurate measurement of learners' self-regulated learning (SRL) in online education is necessary to determine which learners are in need of support and how to best offer support. Trace data is gathered automatically…
Descriptors: Learning Strategies, Online Courses, Electronic Learning, Data Collection
Golden, Cindy – Brookes Publishing Company, 2018
Collecting data on behavior, academic skills, and Individualized Education Plan (IEP) goals is an essential step in showing student progress--but it can also be a complicated, time-consuming process. Take the worry and stress out of data collection with this ultra-practical resource, packed with the tools you need to organize, manage, and monitor…
Descriptors: Data Collection, Information Management, Student Records, Student Behavior
Gartner, Tracy B.; Thomas, Carolyn L.; Geedey, Kevin; Bjorgo-Thorne, Kim; Simmons, Jeffrey A.; Shea, Kathleen L.; Dosch, Jerald J.; Zimmermann, Craig R. – American Biology Teacher, 2020
Increasingly, undergraduate institutions are incorporating original research into the curriculum as a matter of best practice. However, while the practice of science has grown more collaborative, undergraduate research has remained largely confined to single-institution studies. Incorporating long-term, distributed research projects into the…
Descriptors: Undergraduate Students, Biology, Science Instruction, Best Practices
Horn, Michael B.; Fisher, Julia Freeland – Educational Leadership, 2017
The Clayton Christiansen Institute maintains a database of more than 400 schools across the United States that have implemented some form of blended learning, which combines online learning with brick-and-mortar classrooms. Data the Institute has collected over the past six months suggests three trends as this model continues to evolve and mature.…
Descriptors: Blended Learning, Data Collection, Educational Trends, Individualized Instruction
Oliveira, David Manuel Duarte; Pedro, Luís; Santos, Carlos – Smart Learning Environments, 2021
This paper was developed within the scope of a PhD thesis that intends to characterize the use of mobile applications by the students of the University of Aveiro during class time. The main purpose of this paper is to present the results of an initial pilot study that aimed to fine-tune data collection methods in order to gather data that…
Descriptors: Telecommunications, Higher Education, Pilot Projects, Handheld Devices
Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Fudge, Anthea; Pardo, Abelardo; Gentili, Sheridan – Australasian Journal of Educational Technology, 2020
Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of…
Descriptors: Individualized Instruction, Learning Analytics, Data Collection, Student Attitudes
Goldenberg, Lauren B.; Wanta, Violet; Fletcher, Andrew – Learning Professional, 2019
Early literacy is the foundation of academic success and predicts outcomes far beyond elementary school. So when only 30% of 3rd graders in New York City public schools scored proficient on the state test in 2014, district leaders began targeting improvements in literacy instruction in grades K-2. In 2016, the New York City Department of Education…
Descriptors: Emergent Literacy, Grade 3, Elementary School Students, Kindergarten
Nguyen, Quan; Huptych, Michal; Rienties, Bart – Journal of Learning Analytics, 2018
Extensive research in learning science has established the importance of time management in online learning. Recently, learning analytics (LA) has shed further lights on the temporal characteristics of learning by allowing researchers to capture authentic digital footprints of student learning behaviours. Nonetheless, students' timing of…
Descriptors: Time Management, Online Courses, Educational Technology, Technology Uses in Education