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Education Sciences
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Learning Environments
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Learning Environments

A special issue of Education Sciences (ISSN 2227-7102).

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 22822

Special Issue Editor

Assoc. Prof. Teemu Leinonen

E-Mail Website
Guest Editor
Department of Media, Aalto University, FI-00076 Aalto, Finland
Interests: learning environments; new media; design; education inquiry; learning

Special Issue Information

Dear Colleagues,

Learning environments are spaces designed to advance teaching and learning. These spaces can be studied from the perspective of their simultaneous psychological, social, and physical character. Today, these spaces can also be entirely virtual or include virtual components.

Learning environments can be, for instance learner-, community-, or content-centred. They can foster playful learning, project-based learning, independent study, or groupwork. Another important aspect of learning environments regards safety and wellbeing, covering the related psychological, social, and physical issues. Furthermore, in the design and research of learning environments, we may pay attention to accessibility, equity, and inclusion.

For this Special Issue of Educational Science, we invite theoretical, practice-based, practice-led, and empirical studies broadly looking at learning environments from psychological, social, technological, design, and architectural perspectives. The aim is to capture the diversity of research related to learning environments. Especially, we are looking for contributions on innovative learning environment designs.

The themes of this Special Issue include, but are not limited to:

  • Physical learning environments: school and learning space design based on pedagogy
  • Virtual learning environments based on pedagogy
  • Outdoor learning environments based on pedagogy
  • Learning science and learning environment
  • Learning environments for different school subjects and disciplines: languages, math, science, humanities, art and design, technology, engineering, etc.
  • Learning environments for different pedagogical approaches and situations; student-centred, collaborative, active, multi-disciplinary, transdisciplinary, assessment, self-study, posthumanist, etc.
  • Integration of Learning Analytics and Artificial Intelligence into learning environments
  • Comparation of different types of learning environment
  • Safety and well-being and learning environments
  • Accessibility, inclusion, and learning environments
  • Discrimination and learning environments
  • Participatory design of learning environments
  • Methodological questions related to the design and implementation of learning environments

Assoc. Prof. Teemu Leinonen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Learning environments
  • Virtual learning environments
  • Design
  • Pedagogy
  • Research-based practices

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Published Papers (3 papers)

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Research

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13 pages, 726 KiB  
Article
Subjective Well-Being and Its Relation to Academic Performance among Students in Medicine, Dentistry, and Other Health Professions
by Vijay Kumar Chattu, Pradeep Kumar Sahu, Neela Seedial, Gerlisa Seecharan, Amanda Seepersad, Melina Seunarine, Shivanna Sieunarine, Kahamaron Seymour, Samantha Simboo and Arissa Singh
Educ. Sci. 2020, 10(9), 224; https://doi.org/10.3390/educsci10090224 - 28 Aug 2020
Cited by 17 | Viewed by 6784
Abstract
Subjective well-being is defined as a person’s cognitive and affective evaluations of his or her life. This study aims to investigate the differences in the domains of subjective well-being based on gender, type of school, and academic performance. Additionally, the study aimed to [...] Read more.
Subjective well-being is defined as a person’s cognitive and affective evaluations of his or her life. This study aims to investigate the differences in the domains of subjective well-being based on gender, type of school, and academic performance. Additionally, the study aimed to determine the factors (socio-demographic variables, including the academic performance of the students) that are predictive of subjective well-being. Subjective well-being was assessed using a questionnaire which included the Satisfaction with Life Scale (SWLS), which measured the respondent’s life satisfaction, the Scale of Positive and Negative Experience (SPANE), which consisted of six positive and negative emotions, and, lastly, the Flourishing Scale (FS), which measured the respondents’ self-perceived success. Data were collected, transformed into a linear scale, and exported into SPSS version 24, where t-tests, one-way analysis of variance, Pearson correlation, and stepwise regression were performed. Of the total of 535 participants, the majority were females (383 = 71.6%) and studying in a school of medicine (31.8%). With respect to the SWLS and FS, a significant difference was reported among students based on the type of school and their academic performance (p < 0.05). While comparing the differences in the SPANE, a significant difference was recorded based on academic performance. Among the domains of subjective well-being, only the SPANE showed a significant association with academic performance. Greater subjective well-being correlates with higher academic performance, indicating that subjective well-being is an important aspect of a student’s academic life; provisions can be made by paying more attention to those who showed poor academic performance during and at the end of each semester. Full article
(This article belongs to the Special Issue Learning Environments)
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23 pages, 2560 KiB  
Article
Are Physical Experiences with the Balance Model Beneficial for Students’ Algebraic Reasoning? An Evaluation of two Learning Environments for Linear Equations
by Mara Otten, Marja van den Heuvel-Panhuizen, Michiel Veldhuis, Jan Boom and Aiso Heinze
Educ. Sci. 2020, 10(6), 163; https://doi.org/10.3390/educsci10060163 - 17 Jun 2020
Cited by 6 | Viewed by 4824
Abstract
The balance model is often used for teaching linear equation solving. Little research has investigated the influence of various representations of this model on students’ learning outcomes. In this quasi-experimental study, we examined the effects of two learning environments with balance models on [...] Read more.
The balance model is often used for teaching linear equation solving. Little research has investigated the influence of various representations of this model on students’ learning outcomes. In this quasi-experimental study, we examined the effects of two learning environments with balance models on primary school students’ reasoning related to solving linear equations. The sample comprised 212 fifth-graders. Students’ algebraic reasoning was measured four times over the school year; students received lessons in between two of these measurements. Students in Intervention Condition 1 were taught linear equation solving in a learning environment with only pictorial representations of the balance model, while students in Intervention Condition 2 were taught in a learning environment with both physical and pictorial representations of the balance model, which allowed students to manipulate the model. Multi-group latent variable growth curve modelling revealed a significant improvement in algebraic reasoning after students’ participation in either of the two intervention conditions, but no significant differences were found between intervention conditions. The findings suggest that the representation of the balance model did not differentially affect students’ reasoning. However, analyzing students’ reasoning qualitatively revealed that students who worked with the physical balance model more often used representations of the model or advanced algebraic strategies, suggesting that different representations of the balance model might play a different role in individual learning processes. Full article
(This article belongs to the Special Issue Learning Environments)
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Review

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19 pages, 2917 KiB  
Review
Digital Learning Environments in Higher Education: A Literature Review of the Role of Individual vs. Social Settings for Measuring Learning Outcomes
by Elke Kümmel, Johannes Moskaliuk, Ulrike Cress and Joachim Kimmerle
Educ. Sci. 2020, 10(3), 78; https://doi.org/10.3390/educsci10030078 - 18 Mar 2020
Cited by 35 | Viewed by 10369
Abstract
Research on digital learning environments has traditionally applied either an individual perspective or a social perspective to learning. Based on a literature review, we examined to what extent individual or social perspectives determined the learning outcome variables that researchers have used as measurements [...] Read more.
Research on digital learning environments has traditionally applied either an individual perspective or a social perspective to learning. Based on a literature review, we examined to what extent individual or social perspectives determined the learning outcome variables that researchers have used as measurements in existing studies. We analyzed prototypical approaches to operationalize learning settings (individual vs. social) published in peer-reviewed journals and identified their relation to several measures of learning outcomes. We rated n = 356 articles and included n = 246 articles in the final analysis. A total of 159 studies (64.6%) used an individual learning setting, while 87 studies (35.4%) used a social learning setting. As learning outcome measures, we observed self-reports, observable behavior, learning skills, elaboration, personal initiatives, digital activity, and social interactions. The two types of learning settings differed regarding the measurement of elaboration and social interactions. We discuss of the implications of our findings for future research and conclude that researchers should investigate further measures of learning outcomes in digital learning settings. Full article
(This article belongs to the Special Issue Learning Environments)
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