Sustainability

Research

22 pages, 2489 KiB

Open AccessArticle

Teaching on Mars: Some Lessons Learned from an Earth-Bound Study into Community Open Online Courses (COOCs) as a Future Education Model Rooted in Social Justice

by Peter Shukie

Sustainability 2019, 11(24), 6893; https://doi.org/10.3390/su11246893 - 04 Dec 2019

Cited by 2 | Viewed by 4114

Abstract

This paper begins with a playful contention that visions of future Martian colonies provide us not only with spaces for imagining extraplanetary activity. These futuristic considerations also offer us opportunity to reflect on education and technology in the here, planet Earth, and now. [...] Read more.

This paper begins with a playful contention that visions of future Martian colonies provide us not only with spaces for imagining extraplanetary activity. These futuristic considerations also offer us opportunity to reflect on education and technology in the here, planet Earth, and now. The focus of this research was the creation of a learning and teaching platform that was offered freely to anyone with the contention that ‘anyone can teach, anyone can learn’. The platform itself was created using Moodle, as an open-source technology, and WordPress. The focus was on creating a space in which any individual, or group, might create learning spaces for free to share with others, based on social justice and challenging often exclusive, marginalising institutional practice. The project began as a critical response to institutional Massive Open Online courses (MOOCs) that promise widened access to knowledge, while rooted in conventional roles of where knowledge comes from and who teachers should be. The COOCs (Community Open Online Courses) project has now over 1500 registered course creators, and this paper discusses some of the key findings from an initial participatory action research process, involving twenty-five of the initial project users introduces some of the key findings from a research project. While decidedly earth-bound, the findings provide evidence of the benefits of widening who is involved in producing educational technology. The results suggest that widened access and greater awareness of power can help avoid continued inequality and marginalised knowledge as we look to a future that must include us all. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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13 pages, 970 KiB

Open AccessArticle

by Daniel Burgos

Sustainability 2019, 11(24), 6883; https://doi.org/10.3390/su11246883 - 04 Dec 2019

Cited by 6 | Viewed by 2542

Abstract

The number of students opting for online educational platforms has been on the rise in recent years. Despite the upsurge, student retention is still a challenging task, with some students recording low-performance margins on online courses. This paper aims to predict students’ performance [...] Read more.

The number of students opting for online educational platforms has been on the rise in recent years. Despite the upsurge, student retention is still a challenging task, with some students recording low-performance margins on online courses. This paper aims to predict students’ performance and behaviour based on their online activities on an e-learning platform. The paper will focus on the data logging history and utilise the learning management system (LMS) data set that is available on the Sakai platform. The data obtained from the LMS will be classified based on students’ learning styles in the e-learning environment. This classification will help students, teachers, and other stakeholders to engage early with students who are more likely to excel in selected topics. Therefore, clustering students based on their cognitive styles and overall performance will enable better adaption of the learning materials to their learning styles. The model-building steps include data preprocessing, parameter optimisation, and attribute selection procedures. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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15 pages, 571 KiB

Open AccessArticle

Impact of Educational Stage in the Application of Flipped Learning: A Contrasting Analysis with Traditional Teaching

by Santiago Pozo Sánchez, Jesús López Belmonte, Antonio José Moreno Guerrero and Juan Antonio López Núñez

Sustainability 2019, 11(21), 5968; https://doi.org/10.3390/su11215968 - 27 Oct 2019

Cited by 44 | Viewed by 6020

Abstract

The effectiveness of flipped learning depends largely on student typology. This study analyzes the applicability of this approach, according to the characteristics inherent to students based on their educational stage. The objective of the research is to verify the effectiveness of flipped learning [...] Read more.

The effectiveness of flipped learning depends largely on student typology. This study analyzes the applicability of this approach, according to the characteristics inherent to students based on their educational stage. The objective of the research is to verify the effectiveness of flipped learning compared to a traditional methodology during the stages of preschool, primary, and secondary education. For this study, a descriptive and correlational experimental research design was followed, based on a quantitative methodology. Two types of analysis groups (control and experimental) were established in each of the mentioned educational stages. As a data collection instrument, a validated ad hoc questionnaire was applied to a sample of 168 students from the Autonomous City of Ceuta (Spain). The results show that the applicability of flipped learning is more positive in primary and secondary education when compared to a traditional teaching method. However, the results found in preschool education reflect the difficulties in adapting the model to the needs of the students of that stage, due to the difficulties in the autonomous management of digital teaching platforms and the requirement of a minimum level of abstraction to apply this approach. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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24 pages, 837 KiB

Open AccessArticle

Effect of an Instructor-Centered Tool for Automatic Assessment of Programming Assignments on Students’ Perceptions and Performance

by Aldo Gordillo

Sustainability 2019, 11(20), 5568; https://doi.org/10.3390/su11205568 - 10 Oct 2019

Cited by 20 | Viewed by 3845

Abstract

Automated assessment systems are increasingly used in higher education programming courses since the manual assessment of programming assignments is very time-consuming. Although a substantial amount of research work has been done on systems for the automatic assessment of programming assignments, most studies are [...] Read more.

Automated assessment systems are increasingly used in higher education programming courses since the manual assessment of programming assignments is very time-consuming. Although a substantial amount of research work has been done on systems for the automatic assessment of programming assignments, most studies are focused on technical characteristics and further research is needed for examining the effect of using these systems on students’ perceptions and performance. This paper examines the effect of using an instructor-centered tool for automatically assessing programming assignments on students’ perceptions and performance in a web development course at a higher education institution. A total of three data sources were used: a survey to collect data regarding students’ perceptions, and the grades of the student assignment submissions and of a practical programming exam in order to analyze the students’ performance. The results show that the incorporation of the automated assessment tool into the course was beneficial for the students, since it allowed for increasing their motivation, improving the quality of their works, and enhancing their practical programming skills. Nonetheless, a significant percentage of students found the feedback that was generated by the tool hard to understand and of little use, and the generated grades unfair. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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12 pages, 2851 KiB

Open AccessArticle

Painting-Emotion Matching Technology Learning System through Repetition

by Taemin Lee and Sanghyun Seo

Sustainability 2019, 11(16), 4507; https://doi.org/10.3390/su11164507 - 20 Aug 2019

Cited by 2 | Viewed by 3444

Abstract

People’s interest in paintings has increased as artists have easier access to an audience. However, at times, laypersons may not understand the significance of a painting. With the development of computer science, it has become possible to analyze paintings using machines, but some [...] Read more.

People’s interest in paintings has increased as artists have easier access to an audience. However, at times, laypersons may not understand the significance of a painting. With the development of computer science, it has become possible to analyze paintings using machines, but some limitations remain. In this paper, we present a learning tool to help analyze the sensitivity of a given painting. To this end, the proposed system provides users with the ability to predict the emotions expressed by a painting through repeated learning of a matched painting. Using this learning tool, users can improve their ability to understand paintings. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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11 pages, 1176 KiB

Open AccessArticle

Technology-Enhanced Learning: An Optimal CPS Learning Application

by Yu-Hung Chien

Sustainability 2019, 11(16), 4415; https://doi.org/10.3390/su11164415 - 15 Aug 2019

Cited by 7 | Viewed by 2739

Abstract

Collaborative problem-solving (CPS) is highly valued in the sustainability of learning to foster the key soft power of talent for the future. In this study, a CPS learning application was built to train and assess individuals with the aim of increasing CPS skills. [...] Read more.

Collaborative problem-solving (CPS) is highly valued in the sustainability of learning to foster the key soft power of talent for the future. In this study, a CPS learning application was built to train and assess individuals with the aim of increasing CPS skills. For effective learning to take place, several issues need to be carefully considered, and these were investigated while testing the proposed application. This study examined the impact of collaborative interactions (CIs) (human–computer agent (HCA) and human–human (HH) interactions) on the CPS performance of students. Gender and learning styles, which may have interaction effects with CIs on CPS performance, were also explored. The results show that the students’ CPS performance in HCA was significantly greater than that in HH. The interaction effect between gender and CI was not significant. The impact of learning style on CPS performance in HH was not significant. In contrast, in HCA, students with verbal, global, and reflective learning styles performed significantly better on CPS tasks than did students with visual, sequential, and active learning styles. Finally, we discussed the optimal ways to teach CPS and the practical effects of a CPS learning application. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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24 pages, 1731 KiB

Open AccessArticle

A Case Study on English as a Second Language Speakers for Sustainable MOOC Study

by Ismail Duru, Ayse Saliha Sunar, Su White, Banu Diri and Gulustan Dogan

Sustainability 2019, 11(10), 2808; https://doi.org/10.3390/su11102808 - 16 May 2019

Cited by 9 | Viewed by 5097

Abstract

Massive Open Online Courses (MOOCs) have a great potential for sustainable education. Millions of learners annually enrol on MOOCs designed to meet the needs of an increasingly diverse and international student population. Participants’ backgrounds vary by factors including age, education, location, and first [...] Read more.

Massive Open Online Courses (MOOCs) have a great potential for sustainable education. Millions of learners annually enrol on MOOCs designed to meet the needs of an increasingly diverse and international student population. Participants’ backgrounds vary by factors including age, education, location, and first language. MOOC authors address consequent needs by ensuring courses are well-organised. Learning is structured into discrete steps, prioritising clear communication; video components incorporate subtitles. Variability in participants’ language abilities inevitably create barriers to learning, a problem most extreme for those studying in a language which is not their first. This paper investigates how to identify ESL participants and how best to predict factors associated with their course completion. This study proposes a novel method for automatically categorising (English as Primary and Official Language; English as Official but not Primary Language; and English as a second Language groups) 25,598 participants studying FutureLearn “Understanding Language: Learning and Teaching” MOOC using natural language processing. We compared algorithms’ performance when extracting discernible features in participants’ engagement. Engagement in discussions at the end of the first week is one of the strongest predictive features, while overall, learner behaviours in the first two weeks were identified as the most strongly predictive feature. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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17 pages, 371 KiB

Open AccessArticle

Social Media Usage and Tertiary Students’ Academic Performance: Examining the Influences of Academic Self-Efficacy and Innovation Characteristics

by Kingsley Osei Boahene, Jiaming Fang and Frank Sampong

Sustainability 2019, 11(8), 2431; https://doi.org/10.3390/su11082431 - 24 Apr 2019

Cited by 44 | Viewed by 23851

Abstract

The universal growth of social media usage among tertiary students has been linearly associated with academic performance. As social media use continues its constant growth, its application among tertiary students is inevitable. Its influence on academic performance turns out to be an ever [...] Read more.

The universal growth of social media usage among tertiary students has been linearly associated with academic performance. As social media use continues its constant growth, its application among tertiary students is inevitable. Its influence on academic performance turns out to be an ever more important question to think about. Researchers have mixed results, some found social media usage having little to no effect, and others found negative and positive effects on academic performance. Using a sample of 808 students in ten public tertiary institutions, this study makes an effort on how to deal with these differing outcomes and to investigate the effect of social media usage on tertiary students’ academic performance. We explored the relationship of the frequency of students’ use of social media for educational purposes and their academic performance, as measured by their cumulative grade point average (i.e., CGPA) with academic self-efficacy and innovation characteristics as mediator and moderator, respectively. The results revealed that social media usage for educational purposes positively related to academic performance. It also demonstrated that the use of social media can negatively affect academic performance. This study makes it more noticeable the effect of academic self-efficacy as a mediator in further improving the academic performance of students. Additionally, the empirical results of the study demonstrated that the moderating effect of innovation characteristics between social media usage and academic performance was stronger. The practical relevance of the study is to help governments, politicians, policy makers, students, educational institutions, and other stakeholders to carve specific policies, guidelines, and initiatives in support of social media usage as an innovative and effective tool for learning and sustainable academic performance. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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14 pages, 3187 KiB

Open AccessArticle

Analysis and Prediction of Water Quality Using LSTM Deep Neural Networks in IoT Environment

by Ping Liu, Jin Wang, Arun Kumar Sangaiah, Yang Xie and Xinchun Yin

Sustainability 2019, 11(7), 2058; https://doi.org/10.3390/su11072058 - 07 Apr 2019

Cited by 175 | Viewed by 10617

Abstract

This research paper focuses on a water quality prediction model which requires high-quality data. In the process of construction and operation of smart water quality monitoring systems based on Internet of Things (IoT), more and more big data are produced at a high [...] Read more.

This research paper focuses on a water quality prediction model which requires high-quality data. In the process of construction and operation of smart water quality monitoring systems based on Internet of Things (IoT), more and more big data are produced at a high speed, which has made water quality data complicated. Taking advantage of the good performance of long short-term memory (LSTM) deep neural networks in time-series prediction, a drinking-water quality model was designed and established to predict water quality big data with the help of the advanced deep learning (DL) theory in this paper. The drinking-water quality data measured by the automatic water quality monitoring station of Guazhou Water Source of the Yangtze River in Yangzhou were utilized to analyze the water quality parameters in detail, and the prediction model was trained and tested with monitoring data from January 2016 to June 2018. The results of the study indicate that the predicted values of the model and the actual values were in good agreement and accurately revealed the future developing trend of water quality, showing the feasibility and effectiveness of using LSTM deep neural networks to predict the quality of drinking water. Full article

(This article belongs to the Special Issue Technology-Enhanced Learning: Applications, Architectures and Challenges)

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