Session Information
11 ONLINE 52 A, Quality of higher education: Students' skills development
Paper Session
MeetingID: 941 8647 0225 Code: S0YB3u
Contribution
STEM (science, technology, engineering and mathematics) skills have a positive impact on GDP growth and productivity and are increasingly recognised worldwide as essential for national development and productivity, economic competitiveness and social well-being (Bacovic, Andrijasevic, & Pejovic, 2021; Freeman, Marginson, & Tytler, 2019). PISA measures of the quality of science education show that, overall, data have not improved much since 2000 (Bacovic, Andrijasevic, & Pejovic, 2021). The same situation applies also to Latvia: student achievement in science has not changed significantly and is close to the average change in OECD countries (Geske et al., 2020). Successful and qualitative STEM learning requires not only subject-specific skills such as experimentation, observation, inquiry, engineering-technical skills (Evans, 2020; Sen, Ay, & Kiray, 2018), but also cross-cutting skills such as critical thinking, critical reasoning, problem solving, collaboration, civic engagement and digital literacy (Birzina, Pigozne, & Cedere, 2021). These skills are relevant to 21st century skills, for which there is often no common approach to categorisation. Learning skills can also be divided into two broad groups: hard and soft skills. Hard skills are considered to be cognitive learning skills that are necessary for learning the subject content (Henville, 2012, 43). They can be described from two perspectives, i.e., both general and specific to the context in which these skills are used (Putra, et al., 2020). Other researchers (Sen, Ay, & Kiray, 2018) refer to general skills as basic skills such as skills for reading, writing and arithmetic operations. Soft skills refer to personal cross-cutting skills such as social, public speaking and communication skills, friendliness and teamwork and other personality traits that characterise relationships between people (Cimatti, 2016). These can be divided into intrapersonal and interpersonal learning skills.
Based on the classification of learning competences developed by J. Soland, L.S. Hamilton and B.M. Stecher (2013) and complementing it with findings of other researchers (Siekmann and Korbel, 2016; Fan, & Ritz, 2014; Geisinger, 2016; English, 2017; Putra et al., 2020), a classification of learning competences was developed and used by authors in their study. Learning skills were divided into hard skills - cognitive skills which, in turn, were divided into two subgroups: General skills: reading, writing, remembering, numbering, critical and higher order thinking, problem-solving, creativity and STEM discipline specific skills: experimentation, observation, scientific inquiry, engineering technology skills. Soft skills were divided into interpersonal (Communication, Collaboration, Leadership, Teamwork, Dealing with diversity) and intrapersonal (Learning how to learn (metacognition), Intrinsic motivation, Grit, Adaptation (adaptability), Self-development, Self-respect (esteem), Self-management, Self-regulation (direction), Time management).
After summarising the theoretical findings, the question of how the learning skills of Latvian school students compare with the data from the above-mentioned studies was raised. The aim of the study was to investigate the suitability of learning skills acquired at school for studying science at university. To find this out, two research questions were set:
1. What learning skills today's students need to learn in STEM education?
2. What are the opinions of first-year science students at the University of Latvia about the learning skills they have acquired at school to be able to study well?
Method
The study consisted of two parts: a systematic review of two databases (Web of science (WoS) and SCOPUS) was conducted to identify learning skills, and then a survey of first-year science students about their learning skills at school was carried out. 242 first-year science students (male n=50; female n=192) from the University of Latvia participated in the survey between 2018 and 2020. Quantitative and qualitative research was conducted in WoS and SCOPUS databases based on a systematic approach (Booth, Sutton, & Papaioannou, 2016). Keywords "learning skills", then "STEM education" and "Science education" were selected to search for the information. As the second part of the study was aimed at exploring first-year students' views on learning skills at school, the selection was limited to the keywords "school" and "student". The limiting criteria were the time of publication of the articles used in the systematic review, the language, the publication only in scientific journals and conference proceedings, and in the selected databases, excluding those articles that were in both databases. The student survey was conducted in the QuestionPro platform. Students' responses to the open question “What are the three most important learning skills you have acquired by learning at school?” were used for data analysis. Qualitative and quantitative analysis of the data was carried out by coding the data using AQUAD 7.0. To do this a coding system was created with Student Speaker codes (/$Student1.../$Student242) and Conceptual codes that described learning skills cognitively, interpersonally and intrapersonally (Soland, Hamilton, & Stecher, 2013; Fan, & Ritz, 2014; Siekmann & Korbel, 2016; Cimatti, 2016; Geisinger, 2016; English, 2017; Putra et al., 2020).
Expected Outcomes
Findings of the Systematic Review A total of 4899 records were initially found in the two databases. The number of records was limited during the selection process by using limiting keywords. Finally, 23 eligible articles were found in both databases, from which 14 articles that did not meet the criteria were excluded. In the end, 9 articles were retained for further study. The selected articles have been published in conference proceedings between 2017 and 2021. This means that their authors have participated in conferences related to specific STEM subjects, and hence mainly emphasized cognitive skills: subject-specific knowledge for learning science concepts, scientific inquiry, engineering technology design and experimentation, as well as problem-based and project-based approaches that develop students' creativity and high-order thinking skills. Among the interpersonal skills, collaboration and communication are mainly emphasised, and innovative digital communication is highlighted. Time-management, self-efficacy, self-regulation are mentioned as intrapersonal skills, which ensure self-directed learning by emphasizing student's attitudes. Findings of the Empirical Research Intrapersonal skills (n=456): self-management, time-management and self-development are considered by students to be the most important learning skills acquired at school. Interpersonal skills (n=191): communication, cooperation and teamwork skills, as well as public speaking skills were also important for them. Cognitive skills (n=160): high-order thinking, using information search and selection were slightly less mentioned. Prior knowledge plays an important role in the learning process. In addition to STEM subject knowledge, students mentioned the foreign language proficiency. It should be noted that general literacy in reading, writing and numeracy is essential for success at the university, as noted by students. The findings confirm the authors' previous research (Birzina, Cedere&Petersone, 2019) that it is the interpersonal and intrapersonal skills that are important for students in their first year of studies and that they attach importance to these skills when learning at school.
References
Bacovic, M., Andrijasevic, Z.,&Pejovic, B. (2021). STEM Education and Growth in Europe. Journal of the Knowledge Economy, 1-24. Birzina, R., Cedere, D., & Petersone, L. (2019). Factors Influencing the First Year Students’ Adaptation to Natural Science Studies in Higher Education. Journal of Baltic Science Education, 18(3), p. 349-361. doi.org/10.33225/jbse/19.18.349 Birzina, R., Pigozne, T.,&Cedere, D. (2021). Students’ Readiness for STEM Learning within the Context of National Education Reform. Human, Technologies and Quality of Education, 657–752. doi: 10.22364/htqe.2021.52 Booth, A., Sutton, A., & Papaioannou, D. (2016). Systematic approaches to a successful literature review. Los Angeles, CA: Sage. Cedere, D., Birzina, R., Pigozne, T.,&Vasilevskaya, E. (2020). Perceptions of Today’s Young Generation about Meaningful Learning of STEM. Problems of Education in the 21st Century, 78(6), 920-932. doi.org/10.33225/pec/20.78.920 Cimatti, B. (2016). Definition, development, assessment of soft skills and their role for the quality of organizations and enterprises. International Journal for quality research, 10(1). English, L. D. (2017). Advancing elementary and middle school STEM education. International Journal of Science and Mathematics Education, 15(1), 5-24. Evans, C. M. (2020). Measuring student success skills: A review of the literature on collaboration. Dover, NH: National Center for the Improvement of Educational Assessment. Fan, S. C. C.,&Ritz, J. (2014). International views of STEM education. PATT-28 Research into Technological and Engineering Literacy Core Connections, 7-14. Freeman, B., Marginson, S.,&Tytler, R. (2019). An international view of STEM education. In STEM Education 2.0 (pp. 350-363). Brill Sense. Geisinger, K. F. (2016). 21st Century Skills: What Are They and How Do We Assess Them?, Applied Measurement in Education, 29:4, 245-249, DOI: 10.1080/08957347.2016.1209207 Geske, A., Grīnfelds, A., Kangro, A., Kiseļova, R.,&Stūre, B. (2020). Latvijas skolēnu sasniegumi un skolas vide OECD PISA salīdzinājumā / Latvian students' performance and school environment in OECD PISA comparison. Henville, N. (2012). Hard vs soft skills training. Training Journal, 21(2), 41-44. Putra, A. S., Novitasari, D., Asbari, M., Purwanto, A., Iskandar, J., Hutagalung, D.,&Cahyono, Y. (2020). Examine Relationship of Soft Skills, Hard Skills, Innovation and Performance: the Mediation Effect of Organizational Learning. International Journal of Science and Management Studies (IJSMS), 3(3), 27-43. Sen, C., Ay, Z. S.,&Kiray, S. A. (2018). STEM skills in the 21st century education. Research highlights in STEM education, 81-101. Siekmann, G.,&Korbel, P. (2016). Defining “STEM” skills: review and synthesis of the literature. Support document, 2. Soland, J., Hamilton, L. S.,&Stecher, B. M. (2013). Measuring 21st Century Competencies: Guidance for Educators. RAND Corporation
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.