Alejandro Peña-Ayala

Review: Educational data mining: A survey and a data mining-based analysis of recent works

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How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study

In this chapter we present a case study that illustrates how educational data mining (EDM) is able to support the implementation of government policies and assist the labor of public institutions. Specifically, we highlight the current educational reforms in Mexico and focus on one of its main goals: to enhance the education quality. In response, a valuable data source is mined to discover interesting findings what students think about education, family, teachers, and their surroundings. Thus, a brief description of the legal and social context is given, as well as a profile of the students opinions expressed in a national survey is shaped. Moreover, a framework to build an EDM approach is outlined and a sample of the mined results is stated. As a result of the findings generated by the EDM approach, an interpretation is provided to tailor a conceptual view of the observations made by students, as well as some initiatives to deal with the findings. The work concludes with an exposition of the reasons for presenting this kind of work, a comment on the research fulfilled, a viewpoint of the education in Mexico, and some suggestions to support State polices to enhance education.

A Landscape of Learning Analytics: An Exercise to Highlight the Nature of an Emergent Field

Before the increasing efforts for understanding, predicting, and enhancing students’ learning in educational settings, learning analytics (LA) emerges as a candidate research area to tackle such issues. Thus, several work lines have been conducted, as well as diverse conceptual and theoretical perspectives have been arisen. Moreover, quite interesting and useful outcomes have been produced during the LA short lifetime. However, a clear idea of diverse questions is still pending to be given. (e.g., what does learning analytics mean? what are its backgrounds, related domains, and underlying elements? which are the objects of its applications? and what about the trends and challenges to be considered?) This is the reason why the chapter aims at responding those concerns by a sketch of a conceptual scenery that explains the LA background, its underlying domains and nature, including a survey of recent and relevant approaches, and a relation of risks and opportunities.

A Revision of the Literature Concerned with Mobile, Ubiquitous, and Pervasive Learning: A Survey

This chapter tailors a perspective of the work fulfilled in three learning research lines, which besides holding many common attributes also tend to converge to shape mobile, ubiquitous, and pervasive sceneries. Such a junction pursues to spread the traditional classroom and distance settings to open environments, as well as use the surrounding physical and digital objects as learning content that is available to learners at anytime, anywhere, and in any way. In sum, a complete learning environment is recreated to provide formal and informal learning to support academic studies, professional training, and lifelong learning. Thus, in this chapter a description of the mobile, ubiquitous, and pervasive learning (MUP-Learning) arena is presented through the selection of a sample of recent and transcendent works that offer from a conceptual contribution, such as models and frameworks, even empirical approaches oriented to specific domains of study. The sample of works is characterized according to a proposed pattern, as well as organized according to a suggested taxonomy. A profile to describe each work is also stated and a series of statistics are presented, as well as an analysis of the arena is provided to understand the potential and challenges related to the MUP-Learning field.

A Conceptual Model of the Metacognitive Activity

This chapter makes a call for contributing to shape a theoretical and well sounded baseline concerning metacognition. It begins recognizing the fuzzy boundaries of the metacognition field and tailors a profile through a wide collection of related works. Particularly, this research focuses on an essential subject: metacognition models. Thus, a sample of proposals for describing the nature, components, and performance of the metacognition is summarized, and a proposal called Conceptual Model of the Metacognitive Activity (CMMA) is introduced. The CMMA is a conceptual model that depicts the metacognitive activity with the purpose of providing a functional view of how metacognition interacts with object-oriented cognition. Such a model takes into account basic aspects of neurology and biology sciences. Additionally, the autopoiesis property is considered to describe the autonomy and performance of the metacognition. Moreover, an analysis of metacognitive models is outlined and a comparison between them and the CMMA is made in order to shape an overall idea of what metacognition is, and the contribution of the CMMA. In this way, valuable topics are provided to encourage research oriented to build the metacognition basis.

Ubiquitous learning: A systematic review

Abstract Ubiquitous learning, labeled as u–learning, takes advantage of digital content, physical surroundings, mobile devices, pervasive components, and wireless communication to deliver teaching–learning experiences to users at anytime, anywhere, and anyway. U–learning represents an emergent paradigm that spreads education in diverse settings, where users are situated in authentic learning contexts to face immersive experiences in order to accomplish meaningful learning. With the aim at disseminating such a revolutionary arena, this systematic review analyzes its nature, application, and evolution throughout a longitudinal study, where 176 approaches built since 2010 up to the third quarter of 2017 date are gathered, classified, and characterized to disclose labor traits, outcome patterns, and field tendencies. These five results are grounded respectively in a representative collection, a proposed taxonomy, a suggested pattern, statistical interpretations, mining findings, and critical analysis. The conclusions reveal: u–learning is able to transform traditional education provided at classroom level and by e–learning. Principally, this is because students, pertaining to diverse academic levels experience real and authentic settings, are immersed in dual reality sceneries, benefit from context–aware support, learn diverse educational domains, follow suitable learning paradigms, deal with diverse effects, and interact with different devices and technologies in a blended fashion. All of this with the purpose of enhancing users’ apprenticeship.

Student Modeling by Data Mining

This work pursues to find out patterns of characteristics and behaviors of students. Thus, it is presented an approach to mine repositories of student models (SM). The source information embraces students’ personal information and assessment of the use of a Web-based educational system (WBES) by students. In addition, the repositories reveal a profile composed by personal attributes, cognitive skills, learning preferences, and personality traits of a sample of students. The approach mines such repositories and produces several clusters. One cluster represents volunteers who tend to abandon. Another group clusters people who fulfill their commitments. It is concluded that: educational data mining (EDM) produces some findings to depict students that could be considered for authoring content and sequencing teaching-learning experiences.

Problem-solution process by means of a hierarchical metacognitive model

We propose a Metacognitive Model devoted to problem-solving. It stimulates abstraction, modification, and instantiation metacognitive activities. Our model holds a hierarchical structure, a learning paradigm, and a workflow to skills acquisition. Such a model is a reference for problem-solving processes.