Report on SEA-DR IC 2019 accepted abstracts: What insight do we get from them?

Yosep Dwi Kristanto ORCID iD icon https://orcid.org/0000-0003-1446-0422
Universitas Sanata Dharma, Yogyakarta, Indonesia

yosepdwikristanto@usd.ac.id

In Brief

  1. There are more than 200 proposed abstracts that were accepted for the 7th South East Asia Design Research International Conference (SEA-DR IC 2019).
  2. The common topics which appear in the accepted abstracts are mathematics, high school, problem-based learning, design research, PMRI, ethnomathematics, and problem-solving.
  3. There are nearly four hundred authors who are affiliated with 76 institutions contributing to the accepted abstracts.
  4. The institutions of the authors are from Indonesia, Philippines, Brunei Darussalam, Thailand, Sweden, Canada, and South Korea.
  5. The co-authorship and affiliation networks show a relatively high degree of intra- and inter-institutional collaboration among the authors.
  6. The international collaboration degree among authors is small.

Abstract

The present paper gives an overview with regard to the content and co-authorship of the accepted abstracts which have been submitted for the SEA-DR IC 2019. To this end, a content analysis was employed on the titles, abstracts, and keywords which have been submitted to the conference submission system. The social network analysis was also used to capture the co-authorship and affiliation networks derived from the accepted abstracts. The results of the present report provide a list of common topics that appears in the abstracts and the structure of co-authorship and affiliation networks of the contributed authors for the conference. The results are beneficial for all parties in welcoming the SEA-DR IC 2019.

1. Introduction

The SEA-DR IC 2019 will be organized on 25 – 27 July 2019 in Yogyakarta, Indonesia. At the time of writing, the accepted abstracts for the conference have been announced. There are 230 proposed abstracts that have been submitted for the conference via the Open Conference System (OCS), 221 of them were accepted. Nine abstracts were declined since they did not merit to the conference scope and guidelines.

In order to get insight from the accepted abstracts, the present paper will give an overview of the content and co-authorship of the abstracts. The present report has been organized as follows: First, materials and methods in collecting, organizing, and analyzing the data are presented in Section 2. The results of the content and authorship analysis on the accepted abstracts are described in Section 3 and 4, respectively. Section 5 contains the concluding remarks and the significance of the present report for the various parties related to the upcoming conference.

2. Materials and methods

The data construction involves several steps. In the first step, data summary of all accepted abstracts was extracted manually from the conference system. The data consist of several variables, i.e. ID, title, abstract, keywords, authors, and affiliation which are recorded to the Excel and Word documents. The keywords in the extracted data were then corrected so that they are appropriate with the common terms in the education field. For example, the author’s inputted keyword “pedagogic content knowledge” was replaced by “pedagogical content knowledge.” In addition, the last keyword which is preceded by the word “and” were also corrected by deleting the word “and.” The correction process was also applied to the affiliation data in ensuring that one affiliation only has one exact name. For example, many authors inputted their affiliation as “Universitas Sanata Dharma” and “Sanata Dharma University.” In this case, their affiliation was uniformed into “Universitas Sanata Dharma.”

In the second step, the title, abstract, and keywords were analyzed using a web-based text-mining software [1] in order to create frequency distributions of top words, bigrams, and trigrams. The keywords were also analyzed manually using Excel in order to find the most frequent keywords.

In the final step, authors and affiliation entries were analyzed by using descriptive statistics and social network analysis (SNA). The descriptive statistics were employed to find the characteristics of the accepted abstracts quantitatively. In SNA, co-authorship and affiliation networks [2] were utilized in capturing the structure of co-authorship and research collaboration.

In defining co-authorship and affiliation networks, the definition proposed by Yoshikane, Nozawa, and Tsuji [3] was used. The co-authorship and affiliation networks in which the first author’s name and affiliation act as a target of other authors’ name and affiliation in a network edge are defined. The co-authorship and affiliation networks were analyzed by using Gephi Graph Visualization and Manipulation software [4].

3. What is highlighted from the abstracts?

The top words, bigrams, and trigrams of the title and abstracts are presented in Table 1. The table reveals that students and learning are the most mentioned words in the submitted text. It is also worth noting that mathematics, high school, and problem-based learning are popular research topics for the upcoming conference.

Table 1. Top words, bigrams, and trigrams of the title and abstracts

Aside from looking at the title and the abstract, author keywords were also useful resources in investigating the direction of the conference discussions. Figure 1 depicts the five most frequent keywords provided by the authors. Unsurprisingly, design research appears most often, followed by PMRI, problem-based learning, ethnomathematics, and problem-solving. The appearance of problem-based learning in the list is additional evidence of the popularity of this topic for the conference.


Figure 1. The most frequent keywords inputted by the authors

4. Contributing authors and institutions

There are 399 authors extracted from 221 accepted abstracts. The authors are affiliated with 76 institutions. Those institutions come from Indonesia, Philippines, Brunei Darussalam, Thailand, Sweden, Canada, and South Korea, as shown in Figure 2. From those countries, Indonesia contributes 95.2% of the authors which disperse from 19 provinces, as shown in Figure 3. Special Region of Yogyakarta, where the conference takes place, is the province with the highest number of authors, followed by East Java, Bengkulu, Aceh, and West Java.

Geo Map of Authors' Country

Figure 2. Geo map of authors’ country

The authorship observation of the accepted abstracts shows that most of the abstracts were the results of intra- or inter-institutional collaboration. One hundred and forty-three out of 221 abstracts (64.7%) were authored by more than one author, 35 of them are inter-institutional collaboration and 2 of them are multi-national collaboration. The multi-national collaboration in the 2 abstracts involves Universitas Sanata Dharma, SEAMEO QITEP in Mathematics, Khon Kaen University, and Sogang University.

Geo map of Indonesia-affiliated authors’ residence
Figure 3. Geo map of Indonesia-affiliated authors’ residence

Figure 5 shows the co-authorship networks of accepted abstracts. The colours and the size of the nodes represent the communities and the degree of the authors, respectively. The largest community includes Wahyu Widada, Dewi Herawati, and 29 other authors, all of which are affiliated with the same institution, i.e. Universitas Bengkulu.

Co-authorship networks on accepted abstracts

Figure 4. Co-authorship networks on accepted abstracts

Figure 5 shows the affiliation networks that are extracted from the accepted abstracts. There are 7 communities in these networks. The largest community involves Universitas Pendidikan Indonesia and 10 other institutions. All of the institutions in this community come from Indonesia. The second largest community involves Universitas Sanata Dharma and 8 other institutions which come from Indonesia, South Korea, and Thailand. This is the only community consisting of multi-institutional collaboration.

Affiliation networks on accepted abstracts
Figure 5. Affiliation networks on accepted abstracts

5. Final Remarks

This paper examines some important features obtained from the accepted abstracts of the conference. A content analysis of the title, abstract, and keywords found that design research, mathematics, problem-based learning, PMRI, ethnomathematics, and problem-solving are the common topics for the conference. The authorship analysis suggested that most of the accepted abstracts are multi-authored. This result agrees with Koseoglu [5] that multi-authored articles dominated solo work. The domination of multi-authored abstracts shows a high level of collaboration among scholars for the conference. This collaboration has potential in increasing the conference impact for the academic’s society, especially for the educational design research community, since Gazni and Didegah [6] found that the research collaboration positively affects the number of citations. However, the high level of collaboration in the accepted abstracts only happens in intra- and inter-institutions. The international collaborations found in the accepted abstracts are small.

The results give benefits for the conference participants, committee, and SEA-DR consortium. For the participants, the results can be used as the insight in preparing everything to attend the conference. For the committee, the results are useful in order to organize the conference smoothly. The results of the co-authorship network analysis can be used to choose the appropriate reviewers for a specific paper in the review process [7]. For the SEA-DR consortium, the results can be used as the entry point in discussing the future of SEA-DR research community, specifically related to international collaboration.

The results of this paper have limitations since the source of data is the accepted abstracts of the conference. The abstracts still have the possibility to change because they can be revised by the authors.

References

  1. Bhargava R and D’Ignazio C DataBasic DataBasic.io.
  2. Savić M, Ivanović M and Jain LC 2019 Complex Networks in Software, Knowledge, and Social Systems (Cham: Springer International Publishing). https://doi.org/10.1007/978-3-319-91196-0
  3. Yoshikane F, Nozawa T and Tsuji K 2006 Comparative analysis of co-authorship networks considering authors roles in collaboration: Differences between the theoretical and application areas Scientometrics 68 643–55. https://doi.org/10.1007/s11192-006-0113-1
  4. Bastian M, Heymann S and Jacomy M 2009 Gephi: An Open Source Software for Exploring and Manipulating Networks Third International AAAI Conference on Weblogs and Social Media (California: AAAI Publications).
  5. Koseoglu M A 2016 Growth and structure of authorship and co-authorship network in the strategic management realm: Evidence from the Strategic Management Journal BRQ Business Research Quarterly 19 153–70. https://doi.org/10.1016/j.brq.2016.02.001
  6. Gazni A and Didegah F 2011 Investigating different types of research collaboration and citation impact: a case study of Harvard University’s publications Scientometrics 87 251–65. https://doi.org/10.1007/s11192-011-0343-8
  7. Rodriguez M A and Bollen J 2008 An algorithm to determine peer-reviewers Proceedings of the 17th ACM conference on information and knowledge management (New York, NY: ACM) pp 319–28. https://doi.org/10.1145/1458082.1458127

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