This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…

Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…

We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…

Linguistic meaning is generated by the mind and can be expressed in multiple languages. One may assume that equivalent texts/utterances in two languages by means of translation generate equivalent meanings in their readers/hearers. This follows if we assume that meaning calculated from the linguistic input is solely objective in nature. However,…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…

Fuzzy sets have experienced multiple expansions since their conception to enhance their capacity to convey complex information. Intuitionistic fuzzy sets, image fuzzy sets, q-rung orthopair fuzzy sets, and neutrosophic sets are a few of these extensions. Researchers and academics have acquired a lot of information about their theories and methods…

The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…

Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…

Describes NEGOTIATE, an interactive computer model that synthesizes bargaining theories into algorithmic functions capable of simulating complex labor relations. The models employed in the simulation, the instructional dimension of NEGOTIATE, and various applications of the game are discussed. A seven-item reference list is included. (Author/JL)

A study was conducted to investigate learner control of instruction in contrast to response sensitive branching algorithms with respect to two specific types of instructional decisions: (1) whether a student should enter and study a particular instructional module given his score on an associated diagnostic pretest; and (2) when a student should…

The Computerized Decision Training (CDT) system, which focuses on improving and sharpening higher order cognitive skills in judgmental decision making, incorporates an adaptive computer program which learns the student's value structure, and uses this structure to train the student in practical decision making. The application of decision models…

The ESY Analysis Aids are a collection of materials and procedures related to and organized for use in making decisions concerning year-round school program alternatives. They are restricted largely to procedures dealing with the budgetary impact of school calendar manipulation, but can be used as a guide in monitoring progress in an ESY…