Special Issue "Networks Applied in Science Education Research"

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

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 29240

Special Issue Editors

Prof. Dr. Ismo T. Koponen
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Guest Editor
Department of Physics, University of Helsinki, FI-00014 Helsinki, Finland
Interests: complex systems; complex networks; science education
Special Issues, Collections and Topics in MDPI journals
Dr. Terhi Mäntylä
E-Mail Website
Guest Editor
Department of Teacher Education, PO Box 35, University of Jyväskylä, 40014 Jyväskylä, Finland
Interests: didactic physics; didactic reconstruction in the structure of physics knowledge

Special Issue Information

Dear Colleagues,

Applications of networks and network-based methods have recently found their way into science education research in the areas of concept learning, conceptual change, and the sociodynamics of learning. While graph-based approaches, such as concept maps, have a long tradition in science education research, the novel network-based approaches substantially augment and deepen the possibilities to explore students' knowledge structures as well as the sociodynamic relationships involved in teaching and learning. The goal of this Special Issue is to provide a state-of-the-art overview of research in this rapidly expanding area of research.

Prof. Ismo Koponen
Dr. Terhi Mäntylä
Guest Editors

Manuscript Submission Information

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Keywords

  • science education research
  • networks
  • concept learning
  • conceptual change
  • sociodynamics

Published Papers (14 papers)

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Editorial

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Editorial
Editorial: Networks Applied in Science Education Research
Educ. Sci. 2020, 10(5), 142; https://doi.org/10.3390/educsci10050142 - 18 May 2020
Cited by 2 | Viewed by 1846
Abstract
Science education research is, in many ways, involved with exploring relational aspects of diverse elements that affect students’ learning outcomes; at one end, the elements may be concepts to be learned, and at the other end, the relations between students in different types [...] Read more.
Science education research is, in many ways, involved with exploring relational aspects of diverse elements that affect students’ learning outcomes; at one end, the elements may be concepts to be learned, and at the other end, the relations between students in different types of learning settings and environments and, ultimately, how such elements may interact [...] Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)

Research

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Article
Scanning Signatures: A Graph Theoretical Model to Represent Visual Scanning Processes and A Proof of Concept Study in Biology Education
Educ. Sci. 2020, 10(5), 141; https://doi.org/10.3390/educsci10050141 - 15 May 2020
Cited by 1 | Viewed by 1626
Abstract
In this article we discuss, as a proof of concept, how a network model can be used to analyse gaze tracking data coming from a preliminary experiment carried out in a biodiversity education research project. We discuss the network model, a simple directed [...] Read more.
In this article we discuss, as a proof of concept, how a network model can be used to analyse gaze tracking data coming from a preliminary experiment carried out in a biodiversity education research project. We discuss the network model, a simple directed graph, used to represent the gaze tracking data in a way that is meaningful for the study of students’ biodiversity observations. Our network model can be thought of as a scanning signature of how a subject visually scans a scene. We provide a couple of examples of how it can be used to investigate the personal identification processes of a biologist and non-biologist when they are carrying out a task concerning the observation of species-specific characteristics of two bird species in the context of biology education research. We suggest that a scanning signature can be effectively used to compare the competencies of different persons and groups of people when they are making observations on specific areas of interests. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Concept Mapping in Magnetism and Electrostatics: Core Concepts and Development over Time
Educ. Sci. 2020, 10(5), 129; https://doi.org/10.3390/educsci10050129 - 01 May 2020
Cited by 5 | Viewed by 2345
Abstract
Conceptual change theories assume that knowledge structures grow during the learning process but also get reorganized. Yet, this reorganization process itself is hard to examine. By using concept maps, we examined the changes in students’ knowledge structures and linked it to conceptual change [...] Read more.
Conceptual change theories assume that knowledge structures grow during the learning process but also get reorganized. Yet, this reorganization process itself is hard to examine. By using concept maps, we examined the changes in students’ knowledge structures and linked it to conceptual change theory. In a longitudinal study, thirty high-achieving students (M = 14.41 years) drew concept maps at three timepoints across a teaching unit on magnetism and electrostatics. In total, 87 concept maps were analyzed using betweenness and PageRank centrality as well as a clustering algorithm. We also compared the students’ concept maps to four expert maps on the topic. Besides a growth of the knowledge network, the results indicated a reorganization, with first a fragmentation during the unit, followed by an integration of knowledge at the end of the unit. Thus, our analysis revealed that the process of conceptual change on this topic was non-linear. Moreover, the terms used in the concept maps varied in their centrality, with more abstract terms being more central and thus more important for the structure of the map. We also suggest ideas for the usage of concept maps in class. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Student Participation in Online Content-Related Discussion and Its Relation to Students’ Background Knowledge
Educ. Sci. 2020, 10(4), 106; https://doi.org/10.3390/educsci10040106 - 13 Apr 2020
Cited by 5 | Viewed by 2702
Abstract
This paper presents two novel network methods developed for education research. These methods were used to investigate online discussions and the structure of students’ background knowledge in a blended university course for pre-service teachers (n = 11). Consequently, these measures were used for [...] Read more.
This paper presents two novel network methods developed for education research. These methods were used to investigate online discussions and the structure of students’ background knowledge in a blended university course for pre-service teachers (n = 11). Consequently, these measures were used for correlation analysis. The social network analysis of the online discussions was based on network roles defined using triadic motifs instead of more commonly used centrality measures. The network analysis of the background knowledge is based on the Katz centrality measure and Jaccard similarity. The results reveal that both measures have characteristic features that are typical for each student. These features, however, are not correlated when student participation is controlled for. The results show that the structure and extension of a student’s background knowledge does not explain their activity and role in online discussions. The limitations and implications of the developed methods and results are discussed. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Investigating Network Coherence to Assess Students’ Conceptual Understanding of Energy
Educ. Sci. 2020, 10(4), 103; https://doi.org/10.3390/educsci10040103 - 09 Apr 2020
Cited by 1 | Viewed by 1879
Abstract
Conceptual knowledge is a crucial tool for students to understand scientific phenomena. Knowledge about the structure and function of mental concepts potentially helps science educators to foster the acquisition of this tool. Specifically, the coherence of students’ mental concepts is an intensely discussed [...] Read more.
Conceptual knowledge is a crucial tool for students to understand scientific phenomena. Knowledge about the structure and function of mental concepts potentially helps science educators to foster the acquisition of this tool. Specifically, the coherence of students’ mental concepts is an intensely discussed issue within the related conceptual change discourse. While former discussions focused on the question of whether these conceptions are coherent or not, recent approaches describe them as dynamic systems behaving more or less coherently in different situations. In this contribution, we captured this dynamic behavior of individual concepts by means of network analysis. Transcribed video data of 16 pairs of students working on four subsequent experiments on energy were transformed into weighted networks, which in turn were characterized by standardized coherence parameters. These coherence parameters and more basic network parameters were correlated with students’ pre-post scores of a multiple-choice test on the energy concept. We found that the coherence parameter is significantly related to the students’ test scores. Even more intense relations are indicated if networks are calculated solely based on conceptual key terms. Implications as well as methodological constraints of this approach are discussed. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
How Concept Maps with and without a List of Concepts Differ: The Case of Statistics
Educ. Sci. 2020, 10(4), 91; https://doi.org/10.3390/educsci10040091 - 30 Mar 2020
Cited by 3 | Viewed by 1997
Abstract
Concept mapping is a popular tool for knowledge structure assessment. In recent years, both the amount of research about concept maps and their measurement ability have grown. It has been shown that concept maps with different types of tasks, for instance, links between [...] Read more.
Concept mapping is a popular tool for knowledge structure assessment. In recent years, both the amount of research about concept maps and their measurement ability have grown. It has been shown that concept maps with different types of tasks, for instance, links between concepts given or selected by a respondent, provide information about the different aspects of students’ knowledge structure. This study explores features of concept mapping with and without a list of concepts. At first, eleven masters students constructed concept maps with a topic on statistical data analysis and, after three weeks, repeated the task with the same topic and a predefined list of concepts. Both types of concept maps were evaluated using traditional scoring indicators and indicators from the network analysis. All indicators were tested for significant differences, and then the content of these maps was analysed. Results show that the list of concepts forced respondents to construct more connective maps, which is related to a more developed knowledge structure. Moreover, it is easier for them, when including even abstract concepts, to define their role in the domain. However, respondents use concepts and group them in different ways depending on the instruction. It seems that respondents feel a “list stress”, which leads to differences in the content. These findings demonstrate the possibilities of using different concept mapping tasks for learning and assessment. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Pre-Service Teachers’ Declarative Knowledge of Wave-Particle Dualism of Electrons and Photons: Finding Lexicons by Using Network Analysis
Educ. Sci. 2020, 10(3), 76; https://doi.org/10.3390/educsci10030076 - 17 Mar 2020
Cited by 3 | Viewed by 1696
Abstract
Learning the wave-particle dualism of electrons and photons plays a central role in understanding quantum physics. Teaching it requires that the teacher is fluent in using abstract and uncommon terms. We inspect the lexical structures of pre-service teachers’ declarative knowledge about the wave-particle [...] Read more.
Learning the wave-particle dualism of electrons and photons plays a central role in understanding quantum physics. Teaching it requires that the teacher is fluent in using abstract and uncommon terms. We inspect the lexical structures of pre-service teachers’ declarative knowledge about the wave-particle dualism of electrons and photons in the context of double-slit interference. The declarative knowledge is analyzed in the form of a lexical network of terms. We focus on lexical structures because, in teaching and learning, knowledge is communicated mostly through lexical structures, i.e., by speaking and writing. Using the lexical networks, we construct the lexicons used by pre-service teachers to express their knowledge of electrons and photons in the context of double-slit interference. The lexicons consist of eight different key terms, each representing a set of closely-related or synonymous terms. The lexicons by 14 pre-service teachers reveal remarkable variation and differences, and are strongly context-dependent. We also analyzed lexicons corresponding to two didactically-oriented research articles on the same topic and found that they also differ. Lexicons paralleling both texts are found among the pre-service teachers’ lexicons. However, only some of the pre-service teachers use such rich vocabulary as would indicate multi-faceted understanding of quantum entities. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Combining Surveys and Sensors to Explore Student Behaviour
Educ. Sci. 2020, 10(3), 68; https://doi.org/10.3390/educsci10030068 - 10 Mar 2020
Viewed by 1613
Abstract
Student belongingness is important for successful study paths, and group work forms an important part of modern university physics education. To study the group dynamics of introductory physics students at the University of Helsinki, we collected network data from seven laboratory course sections [...] Read more.
Student belongingness is important for successful study paths, and group work forms an important part of modern university physics education. To study the group dynamics of introductory physics students at the University of Helsinki, we collected network data from seven laboratory course sections of approximately 20 students each for seven consecutive weeks. The data was collected via the SocioPatterns platform, and supplemented with students’ major subject, year of study and gender. We also collected the Mechanics Baseline Test to measure physics knowledge and the Colorado Learning Attitudes about Science Survey to measure attitudes. We developed metrics for studying the small networks of the laboratory sessions by using connections of the teaching assistant as a constant. In the network, we found both demographically homogeneous and heterogeneous groups that are stable. While some students are consistently loosely connected to their networks, we were not able to identify risk factors. Based on our results, the physics laboratory course is equally successful in building strongly connected groups regardless of student demographics in the sections or the formed small groups. SocioPatterns supplemented with surveys thus provides an opportunity to look into the dynamics of students’ social networks. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Network Analysis of Survey Data to Identify Non-Homogeneous Teacher Self-Efficacy Development in Using Formative Assessment Strategies
Educ. Sci. 2020, 10(3), 54; https://doi.org/10.3390/educsci10030054 - 03 Mar 2020
Viewed by 2044
Abstract
In a European project about formative assessment, Local Working Groups (LWGs) from six participating countries made use of a format for teacher-researcher collaboration. The activities in each LWG involved discussions and reflections about implementation of four assessment formats. A key aim was close [...] Read more.
In a European project about formative assessment, Local Working Groups (LWGs) from six participating countries made use of a format for teacher-researcher collaboration. The activities in each LWG involved discussions and reflections about implementation of four assessment formats. A key aim was close collaboration between teachers and researchers to develop teachers’ formative assessment practices, which were partially evidenced with changes in attributes of self-efficacy. The research question was: to what extent do working with formative assessment strategies in collaboration with researchers and other teachers differentially affect individual self-efficacy beliefs of practicing teachers across different educational contexts? A 12-item teacher questionnaire, with items selected from a commonly used international instrument for science teaching self-efficacy, was distributed to the participating teachers before and after their work in the LWGs. A novel method of analysis using networks where participants from different LWGs were linked based on the similarities of their answers, revealed differences between empirically identified groups and larger super groups of participants. These analyses showed, for example, that one group of teachers perceived themselves to have knowledge about using formative assessment but did not have the skills to use it effectively. It is suggested that future research and development projects may use this new methodology to pinpoint groups, which seem to respond differently to interventions and modify guidance or instruction accordingly. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Measuring Characteristics of Explanations with Element Maps
Educ. Sci. 2020, 10(2), 36; https://doi.org/10.3390/educsci10020036 - 11 Feb 2020
Cited by 1 | Viewed by 1633
Abstract
What are the structural characteristics of written scientific explanations that make them good? This is often difficult to measure. One approach to describing and analyzing structures is to employ network theory. With this research, we aim to describe the elementary structure of written [...] Read more.
What are the structural characteristics of written scientific explanations that make them good? This is often difficult to measure. One approach to describing and analyzing structures is to employ network theory. With this research, we aim to describe the elementary structure of written explanations, their qualities, and the differences between those made by experts and students. We do this by converting written explanations into networks called element maps and measure their characteristics: size, the ratio of diameter to size, and betweenness centrality. Our results indicate that experts give longer explanations with more intertwinement, organized around a few central key elements. Students’ explanations vary widely in size, are less intertwined, and often lack a focus around key elements. We have successfully identified and quantified the characteristics that can be a starting point for guiding students towards generating expert-like written explanations. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Between Social and Semantic Networks: A Case Study on Classroom Complexity
Educ. Sci. 2020, 10(2), 30; https://doi.org/10.3390/educsci10020030 - 01 Feb 2020
Cited by 5 | Viewed by 2167
Abstract
Classrooms are complex in their real sets. To understand such sets and their emergent patterns, network approach provides useful theoretical and methodological tools. In this work, we used network approach to explore two domains of complexity in a classroom: the interpersonal domain, via [...] Read more.
Classrooms are complex in their real sets. To understand such sets and their emergent patterns, network approach provides useful theoretical and methodological tools. In this work, we used network approach to explore two domains of complexity in a classroom: the interpersonal domain, via social networks; and the representational domain, through collective semantic networks. This work is grounded in both Social Network Analyses and Social Representation Theory for gathering information from interpersonal and representational domains. We investigated a physics high school classroom by proceeding sociometric tests and by using words freely evoked by students to explore relations between students’ dyad’s weights, in social networks, and emerging consensus in semantic networks. Our findings showed closer relations between social ties’ weight and consensus formed on intra-school representational objects, while consensus on extra-school representational objects is less dependent on the classroom interpersonal ties’ strength. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Transferring Knowledge in a Knowledge-in-Use Task—Investigating the Role of Knowledge Organization
Educ. Sci. 2020, 10(1), 20; https://doi.org/10.3390/educsci10010020 - 16 Jan 2020
Cited by 5 | Viewed by 2038
Abstract
Knowledge-in-Use, i.e., the ability to apply what one has learned, is a major goal of education and involves the ability to transfer one’s knowledge. While some general principles of knowledge transfer have been revealed, the literature is full of inconclusive results and it [...] Read more.
Knowledge-in-Use, i.e., the ability to apply what one has learned, is a major goal of education and involves the ability to transfer one’s knowledge. While some general principles of knowledge transfer have been revealed, the literature is full of inconclusive results and it remains hard to predict successful transfer. However, research into expertise suggests that how one organizes one’s knowledge is critical for successful transfer. Drawing on data from a larger study on the learning of energy, we employed network analysis to investigate how the organization of students’ knowledge about energy influenced their ability to transfer and what role achievement goal orientation may have played in this. We found that students that had more coherently organized knowledge networks were more successful in transfer. Furthermore, we also found a connection between mastery goal orientation and the organization of students’ knowledge networks. Our results extend the literature by providing evidence for a direct connection between the organization of students’ knowledge networks, their success in transfer, and their goal orientation and hint at the complexities in the relationship between mastery approach goal orientation and successful transfer beyond what is reported in the literature. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Article
Forma Mentis Networks Reconstruct How Italian High Schoolers and International STEM Experts Perceive Teachers, Students, Scientists, and School
Educ. Sci. 2020, 10(1), 17; https://doi.org/10.3390/educsci10010017 - 06 Jan 2020
Cited by 7 | Viewed by 2168
Abstract
This study investigates how students and researchers shape their knowledge and perception of educational topics. The mindset or forma mentis of 159 Italian high school students and of 59 international researchers in science, technology, engineering and maths (STEM) are reconstructed through forma mentis [...] Read more.
This study investigates how students and researchers shape their knowledge and perception of educational topics. The mindset or forma mentis of 159 Italian high school students and of 59 international researchers in science, technology, engineering and maths (STEM) are reconstructed through forma mentis networks, i.e., cognitive networks of concepts connected by free associations and enriched with sentiment labels. The layout of conceptual associations between positively/negatively/neutrally perceived concepts is informative on how people build their own mental constructs or beliefs about specific topics. Researchers displayed mixed positive/neutral mental representations of “teacher”, “student” and, “scientist”. Students’ conceptual associations of “scientist” were highly positive and largely non-stereotypical, although links about the “mad scientist” stereotype persisted. Students perceived “teacher” as a complex figure, associated with positive aspects like mentoring/knowledge transmission but also to negative sides revolving around testing and grading. “School” elicited stronger differences between the two groups. In the students’ mindset, “school” was surrounded by a negative emotional aura or set of associations, indicating an anxious perception of the school setting, mixing scholastic concepts, anxiety-eliciting words, STEM disciplines like maths and physics, and exam-related notions. Researchers’ positive stance of “school” included concepts of fun, friendship, and personal growth instead. Along the perspective of Education Research, the above results are discussed as quantitative evidence for test- and STEM anxiety co-occurring in the way Italian students perceive education places and their actors. Detecting these patterns in student populations through forma mentis networks offers new, simple to gather yet detailed knowledge for future data-informed intervention policies and action research. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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Commentary
Applications of Network Science to Education Research: Quantifying Knowledge and the Development of Expertise through Network Analysis
Educ. Sci. 2020, 10(4), 101; https://doi.org/10.3390/educsci10040101 - 08 Apr 2020
Cited by 13 | Viewed by 2603
Abstract
A fundamental goal of education is to inspire and instill deep, meaningful, and long-lasting conceptual change within the knowledge landscapes of students. This commentary posits that the tools of network science could be useful in helping educators achieve this goal in two ways. [...] Read more.
A fundamental goal of education is to inspire and instill deep, meaningful, and long-lasting conceptual change within the knowledge landscapes of students. This commentary posits that the tools of network science could be useful in helping educators achieve this goal in two ways. First, methods from cognitive psychology and network science could be helpful in quantifying and analyzing the structure of students’ knowledge of a given discipline as a knowledge network of interconnected concepts. Second, network science methods could be relevant for investigating the developmental trajectories of knowledge structures by quantifying structural change in knowledge networks, and potentially inform instructional design in order to optimize the acquisition of meaningful knowledge as the student progresses from being a novice to an expert in the subject. This commentary provides a brief introduction to common network science measures and suggests how they might be relevant for shedding light on the cognitive processes that underlie learning and retrieval, and discusses ways in which generative network growth models could inform pedagogical strategies to enable meaningful long-term conceptual change and knowledge development among students. Full article
(This article belongs to the Special Issue Networks Applied in Science Education Research)
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