Reflections on Personal Learning Environments: Theory and Practice

Archee, Ray

doi:10.1016/j.sbspro.2012.09.520

Cited by 18 publications

(20 citation statements)

References 16 publications

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“…RS are not fully implemented yet in the discipline of e-learning, although there are frameworks which are already conceptualized and presented. In fact, the success and stability of PLEs, which mainly operate on digital space platforms, are still yet to be seen (Archee, 2012).…”

Section: Figure 1: Model Of Traditional Learning Management Systemmentioning

confidence: 99%

Learning Management System with Prediction Model and Course-content Recommendation Module

Evale

2017

JITE:Research

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Aim/Purpose: This study is an attempt to enhance the existing learning management systems today through the integration of technology, particularly with educational data mining and recommendation systems. Background: It utilized five-year historical data to find patterns for predicting student performance in Java Programming to generate appropriate course-content recommendations for the students based on their predicted performance. Methodology : The author used two models for the system development: these are the Fayyad knowledge discovery in databases (KDD) process model for the data mining phase and the evolutionary prototyping for system development. WEKKA and SPSS were used to find meaningful patterns in the historical data, while Ruby on Rails platform was used to develop the software. Contribution: The contribution of this study is the development of an LMS architecture that can be used to augment the capabilities of the existing systems by integrating a data mining technique for modelling the leaners profile; developing of an algorithm for generating predictions; and making the most appropriate recommendations for the learners based on prior knowledge and learning styles. Findings: The result shows that J48 was the best data mining algorithm to be implemented for finding patterns in the data sets used in this study. Attributes such as age, gender, class schedule, and grades in other programming subjects were found relevant in predicting student performance in Java. Recommendations for Practitioners : It is recommended that collaboration between the academe and IT industry be strengthened to develop a more advanced LMS which could enhance classroom teaching and improve the learning process. Recommendation for Researchers: Combination of multiple algorithm in classifying data set is recommended to further improve the algorithm and rule sets of prediction. Inclusion of intrinsic attributes as part of data set aside from personal and academic records is also recommended. Impact on Society : This LMS can be used to produce independent learners. Future Research: Study about the impact of implementing this LMS in classroom environment will be conducted on the second phase.

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Section: Figure 1: Model Of Traditional Learning Management Systemmentioning

confidence: 99%

Learning Management System with Prediction Model and Course-content Recommendation Module

Evale

2017

JITE:Research

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“…It has been frequently stated that an efficient, personalized and satisfactory PLE is a positive factor that assists individuals to set their learning goals, look for and organize content, communicate with other persons, and evaluate their own learning actions (Archee, 2012;Chaves, Trujillo, & López, 2015;Chaves, Trujillo, & López, 2016;Dabbagh & Kitsantas, 2012;Ebner & Taraghi, 2010;Johnson & Sherlock, 2014). …”

Section: Personal Learning Environments (Ples)mentioning

confidence: 99%

“…In fact, researchers and theorists in the area of PLEs indicate the importance of studying and evaluating the entire process involved in student PLEs, since this environment is better developed when conscientious and self-regulated use of its tools occurs, and even more so if there is support by classmates, teachers and other actors in the educational community (Archee, 2012;Dabbagh & Kitsantas, 2012).…”

Section: Importance Of the Studymentioning

confidence: 99%

Actions and achievements of self-regulated learning in personal environments. Research on students participating in the Graduate Program in Preschool Education at the University of Granada

Chaves-Barboza

Torres

Núñez

et al. 2017

J. New Approaches Educ. Res.

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This paper is intended to study the self-regulated learning (SRL) process in personal learning environments (PLEs) among students participating in the Graduate Program for Preschool Education at the University of Granada (Spain). The study is focused on self-regulatory actions carried out by students, and on their self-regulated learning achievements, during the phases of action and reflection of this process. A Likert scale questionnaire was applied to a random cluster sample of the population. Descriptive and inferential statistical analyses were performed based on the collected data, as were non-parametric correlation and analysis of variance tests. The results confirm the importance of individual learning in the self-regulated process, and highlight the importance of digital tools in all three phases of self-regulation. Furthermore, the results show that teachers' suggestions are related to the use of digital tools and recording of reflections on the learning process, and establish relationships between learning management tools and cognitive and metacognitive processes. The results also permit classification of students into three subgroups, based on their achievements. Analyses are consistent with the theory that explains the cyclical nature of self-regulated learning and the influence of social relationships on individual self-regulatory processes.

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“…Los profesores, los expertos y las redes sociales son fundamentales para lograr que el PLE, de cada individuo, sea cada vez más eficiente, personalizado y satisfactorio (Ebner y Taraghi, 2010;Godwin-Jones, 2009;Dabbagh y Kitsantas, 2012;Archee, 2012); en este sentido, es posible hablar de una responsabilidad global.…”

Section: El Estudio Realizadounclassified

Autorregulación del Aprendizaje en Entornos Personales de Aprendizaje en el Grado de Educación Primaria de la Universidad de Granada, España

2015

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* Autor a quien debe ser dirigida la correspondencia.Recibido Dic. 9, 2014; Aceptado Ene. 20, 2015; Versión final recibida Mar. 9, 2015 Resumen El objetivo del estudio es analizar el proceso de autorregulación del aprendizaje en entornos personales de aprendizaje. El análisis se enfoca en acciones realizadas y logros obtenidos por los estudiantes durante las fases de actuación y de reflexión de este proceso. Se aplicó un cuestionario, tipo escala Likert, a una muestra aleatoria por conglomerados del grado en Educación Primaria de la Universidad de Granada en España. Sobre los datos se realizan análisis descriptivos e inferenciales, también pruebas no paramétricas de correlaciones y de varianzas. Los resultados muestran que las herramientas digitales y los profesores son elementos importantes en el proceso de autorregulación del aprendizaje. En general, la población es exitosa en ambas fases de este proceso, también hay subgrupos de estudiantes que sobresalen por sus logros. Se concluye que el uso adecuado de las herramientas digitales del entorno personal de aprendizaje favorece la autorregulación del aprendizaje en ambas fases. Palabras clave: autorregulación del aprendizaje, entornos personales de aprendizaje, herramientas digitales Self-regulated Learning in Personal Learning Environments on the Grade of Elementary Education, University of Granada, Spain AbstractThe objective of the study is to analyze the process of self-regulation of the learning in personal learning environments. The analysis focuses on actions taken and achievements made of students during the phases of action and self-reflection of this process. A Likert scale type questionnaire was applied to a random cluster sample from the degree in Elementary Education of the University of Granada in Spain. The study performed descriptive and inferential analysis of the data, non-parametric tests of correlations and variances. The results show that digital tools and the teachers are important elements in the process of selfregulated learning. In general, the population is successful in both phases of this process. There are also subgroups of students who stand out for their achievements. It is concluded that proper use of digital tools of personal learning environment favors the self-regulation of the learning process in both phases.

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Reflections on Personal Learning Environments: Theory and Practice

Cited by 18 publications

References 16 publications

Learning Management System with Prediction Model and Course-content Recommendation Module

Learning Management System with Prediction Model and Course-content Recommendation Module

Actions and achievements of self-regulated learning in personal environments. Research on students participating in the Graduate Program in Preschool Education at the University of Granada

Autorregulación del Aprendizaje en Entornos Personales de Aprendizaje en el Grado de Educación Primaria de la Universidad de Granada, España

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