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The well-being of software engineers is increasingly under strain due to the high-stress nature of their roles, which involve complex problem-solving, tight deadlines, and the pressures of rapidly evolving technologies. Despite increasing…

Software Engineering · Computer Science 2025-04-03 Cristina Martinez Montes , Birgit Penzenstadler , Robert Feldt

Graduation and dropout rates have always been a serious consideration for educational institutions and students. High dropout rates negatively impact both the lives of individual students and institutions. To address this problem, this…

Machine Learning · Computer Science 2023-10-18 Sean Kim , Eliot Yoo , Samuel Kim

Student mental health is an increasing concern in academic institutions, where stress can severely impact well-being and academic performance. Traditional assessment methods rely on subjective surveys and periodic evaluations, offering…

Machine Learning · Computer Science 2025-08-05 Md Sultanul Islam Ovi , Jamal Hossain , Md Raihan Alam Rahi , Fatema Akter

Algorithms deployed in education can shape the learning experience and success of a student. It is therefore important to understand whether and how such algorithms might create inequalities or amplify existing biases. In this paper, we…

Computers and Society · Computer Science 2022-12-21 Jade Maï Cock , Muhammad Bilal , Richard Davis , Mirko Marras , Tanja Käser

The motivation of this work is to improve the performance of standard stacking approaches or ensembles, which are composed of simple, heterogeneous base models, through the integration of the generation and selection stages for regression…

Machine Learning · Statistics 2014-03-31 Roberto Aldave , Jean-Pierre Dussault

Scoring models support decision-making in financial institutions. Their estimation and evaluation are based on the data of previously accepted applicants with known repayment behavior. This creates sampling bias: the available labeled data…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive…

Computers and Society · Computer Science 2024-07-12 Denisa Gándara , Hadis Anahideh , Matthew P. Ison , Lorenzo Picchiarini

Predicting student performance is key in leveraging effective pre-failure interventions for at-risk students. As educational data grows larger, more effective means of analyzing student data in a timely manner are needed in order to provide…

Machine Learning · Computer Science 2023-10-10 Thomas Trask

Preventing student dropout is a major challenge in higher education and it is difficult to predict prior to enrolment which students are likely to drop out and which students are likely to succeed. High School GPA is a strong predictor of…

Computers and Society · Computer Science 2025-09-23 K. F. B. Soppe , A. Bagheri , S. Nadi , I. G. Klugkist , T. Wubbels , L. D. N. V. Wijngaards-De Meij

The purpose of the paper is to determine the opportunities and challenges that lead to cloud computing adoption by SMMEs in South Africa by looking at the factors that influence adoption. The TOE framework is used to contextualize the…

Computers and Society · Computer Science 2021-08-24 Simphiwe S. Sithole , Ephias Ruhode

Over the past decade, an explosion in the availability of education-related datasets has enabled new computational research in education. Much of this work has investigated digital traces of online learners in order to better understand and…

Computers and Society · Computer Science 2023-01-16 Nabeel Gillani , Rebecca Eynon

Machine-learning algorithms have gained popularity in recent years in the field of ecological modeling due to their promising results in predictive performance of classification problems. While the application of such algorithms has been…

Machine Learning · Statistics 2019-10-07 Patrick Schratz , Jannes Muenchow , Eugenia Iturritxa , Jakob Richter , Alexander Brenning

Inferring individualised treatment effects from observational data can unlock the potential for targeted interventions. It is, however, hard to infer these effects from observational data. One major problem that can arise is covariate shift…

Machine Learning · Computer Science 2024-04-25 Damian Machlanski , Spyros Samothrakis , Paul Clarke

Higher education provides a solid theoretical and practical, but mostly technical, background for the aspiring software developer. Research, however, has shown that graduates still fall short of the expectations of industry. These…

Software Engineering · Computer Science 2019-11-05 Wouter Groeneveld , Joost Vennekens , Kris Aerts

With the recent implementation of the K to 12 Program, academic institutions, specifically, Colleges and Universities in the Philippines have been faced with difficulties in determining projected freshmen enrollees vis-a-vis decision-making…

Computers and Society · Computer Science 2024-09-05 Dr. Joseph A. Esquivel , James A. Esquivel

Sales forecasts are crucial for the E-commerce business. State-of-the-art techniques typically apply only univariate methods to make prediction for each series independently. However, due to the short nature of sales times series in…

Machine Learning · Statistics 2019-06-03 Rémy Garnier , Arnaud Belletoile

Although there has been significant research in boosting of weak learners, there has been little work in the field of boosting from strong learners. This latter paradigm is a form of weighted voting with learned weights. In this work, we…

Machine Learning · Computer Science 2020-12-22 Matthew A. Reyna , Gari D. Clifford

Endogenous, ideas-led, growth theory and agent based modelling with neighbourhood effects literature are crossed. In an economic overlapping generations framework, it is shown how social interactions and neighbourhood effects are of vital…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Tanya Araujo , Miguel St. Aubyn

We present a unified probabilistic gradient boosting framework for regression tasks that models and predicts the entire conditional distribution of a univariate response variable as a function of covariates. Our likelihood-based approach…

Machine Learning · Statistics 2022-04-05 Alexander März , Thomas Kneib

There is a critical need to develop new educational technology applications that analyze the data collected by universities to ensure that students graduate in a timely fashion (4 to 6 years); and they are well prepared for jobs in their…

Machine Learning · Computer Science 2017-09-19 Zhiyun Ren , Xia Ning , Huzefa Rangwala