This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

Supervision models are fundamental to our supervision practices and criticized for lacking empirical support. As a data-driven approach based on research with expert supervisors, Cohesive Model of Supervision unifies existing models' central premises in a meaningful manner and emphasizes the understated areas of supervision practice.

Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…

Human resources training is considered an effective solution in empowering human resources. Organizations try to have effective educational planning for this precious resource by identifying shortcomings through a need assessment. This study provides a model based on organizational data analysis to achieve a unique and appropriate training…

State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…

With the rapid development of internet technology, the importance of data in various industries has become increasingly prominent. However, in the field of domestic education, especially the research on teaching quality evaluation is relatively sparse. This paper aims to build an evaluation model of physical education teaching quality with big…

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…

In this paper, we put forward the OTTO Model as a means for developing data literacy in pre-service teacher education. The OTTO Model was developed using a combination of quantitative and qualitative data drawn from a three-year study investigating the nature and development of pre-service teachers' data literacy. The aim of the study was to…

As information literacy and data-driven program evaluations have become growing obsessions within academic institutions, how might liberal arts and humanities programmes engage students in both critical and creative explorations of contemporary human-data relations? Inspired by the variety of metaphors that currently shape human-data relations and…

Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…

One of the essential problems, in educational data mining, is to predict students' performance on future learning materials, such as problems, assignments, and quizzes. Pioneer algorithms for predicting student performance mostly rely on two sources of information: students' past performance, and learning materials' domain knowledge model. The…

Sentiment Analysis is a field of Natural Language Processing which aims at classifying the author's sentiment in text. This paper first describes a sentiment analysis model for students' comments about professor performance. The model achieved impressive results for comments collected from student surveys conducted at a private university in…

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…

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…