Examining Individuals’ Utilization of SPOC: Extending the Task-Technology Fit Model with Online and Offline Perspective

Small Private Online Course (SPOC) platform enables individuals to carry out their learning tasks both online and offline. In order to understand individuals’ utilization of SPOC, this study develops a research model to examine the joint influences of three types of perceived fit manifested in perceived technology-task fit (TTF), perceived individual-technology fit (ITF) and perceived online-offline fit (OOF). A survey was conducted in a famous university of China and 371 data were collected from students who selected courses on the SPOC platform. Structural equation modelling method was used to examine the research model. The empirical results suggest that ITF is the most significant antecedent of individual performance expectancy, followed by OOF and TTF. Moreover, individual performance expectancy has a positive influence on user satisfaction and individuals’ continuance intention in the SPOC platform. A post-hoc analysis further indicates that student’s GPA positively moderates the relationship between online participation behavior and course performance. This study extends the traditional perceived fit framework by introducing perceived online-offline fit, and uncovers the antecedents and outcomes of individuals’ utilization in the emerging research context of SPOC

SPOC online video learning clustering analysis: Identifying learners' group behavior characteristics

With the widespread of Small Private Online Courses (SPOC) in colleges and universities, course organizers who provide high-quality personalized course activities need to understand learners' learning status and characteristics, and then optimize the course teaching. However, little research has been done on different learners' group behavior characteristics, such as which indicators can reflect learner groups' behavior, and what are the typical behavior characteristics of different learner groups. In this work, we established a Python Language Foundation self-built SPOC course, and 109 undergraduates' learning behavior data were collected and analyzed. From 74-dimensional behavior log data consisting of 72 video-viewing, course video score, and comprehensive score, Principal Component Analysis was performed to reduce dimensionality. Agglomerative hierarchical clustering was used to divide learners into different categories, and the results showed that 15 groups are clustered. According to the analysis of the four indicators for group characteristics, which are the completion and viewing-stability of task-point videos, unit test excellence, and comprehensive score, it is identified into five primary types, including positive type, regular type, negative type, semi-negative type, and a fluctuation type. Experiments conducted on a real data set across different academic years and courses show that the proposed approach has better clustering accuracy and practicability. It is expected that this work may be used to strengthen the personalized learning support services system in educational institutions and develop a tool that integrates exploration and analysis work onto the web platform

A Review of Data Mining in Personalized Education: Current Trends and Future Prospects

Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness. The integration of AI in educational platforms provides insights into academic performance, learning preferences, and behaviors, optimizing the personal learning process. Driven by data mining techniques, it not only benefits students but also provides educators and institutions with tools to craft customized learning experiences. To offer a comprehensive review of recent advancements in personalized educational data mining, this paper focuses on four primary scenarios: educational recommendation, cognitive diagnosis, knowledge tracing, and learning analysis. This paper presents a structured taxonomy for each area, compiles commonly used datasets, and identifies future research directions, emphasizing the role of data mining in enhancing personalized education and paving the way for future exploration and innovation.Comment: 25 pages, 5 figure

Percepción de los estudiantes de una escuela de negocios sobre el valor pedagógico del recurso SPOC en la metodología de aula invertida

La presente investigación tuvo como objetivo el análisis, desde las percepciones de los estudiantes de la maestría en administración de empresas de la escuela de negocios de una universidad privada en la ciudad de Lima, con respecto al valor pedagógico del recurso llamado SPOC, implementado bajo la metodología del aula invertida (flipped classroom). Su propósito fundamental fue indagar si dicho recurso genera compromiso y mejora el rendimiento académico, derivados del uso y aprovechamiento del SPOC utilizado como contenido teórico previo a las clases regulares de un programa académico y conocer la valoración con respecto a esta metodología. La investigación surgió como un estudio de caso, con un enfoque cualitativo, de carácter exploratorio, abierto, flexible e inductivo, en el cual se empleó la técnica de recolección de data mediante entrevistas semi estructuradas para el recojo de información. Los resultados de la investigación indicaron que, los estudiantes asignaron al recurso SPOC un alto valor pedagógico como herramienta de adquisición de base teórica, el cual era capaz de crear compromiso en el estudiante, dándole contexto y guía, a pesar de no valorar positivamente el formato de entrega del recurso como aula invertida. Como acción derivada de los resultados encontrados, la institución avala el uso del recurso SPOC como parte del modelo de aprendizaje blended mediante la programación de actividades no presenciales.The main objective of this research was the analysis, through the perceptions of MBA students from a private Business School in Lima, of the pedagogical value of the SPOC resource, implemented within the ‘flipped classroom’ learning methodology. The main purpose was to inquire if this resource generates student engagement and improves academic performance, resulting from the use and benefits of SPOC used as theoretical content prior to scheduled academic classes, and assess the perceived value of this methodology. This research includes the analysis of a case study using a qualitative, exploratory, open, flexible and inductive approach, using data collection techniques applied to semi structured interviews. Research results indicate that students assigned to this resource consider it to be of high pedagogical value as a base theoretical acquisition tool and as a means of increasing student engagement, providing context and guidance, although they did not rate the flipped classroom delivery format positively. As a result of these findings, the institution endorses the use of the SPOC resource as part of the blended learning model.Tesi