In today’s world, scientifically literate people are needed to solve problems and make responsible decisions in science, medicine, and other areas important for society (OECD, 2019). This suggests that learning in science subjects needs to equip students not only with the necessary knowledge, but to promote the application of knowledge, plus the gaining of 21st-century skills and associated values (Cipková et al., 2020). A worldwide concern in science education is perceiving learning as a series of disconnected knowledge acquisitions, which impacts students’ interest in science (Author 1 et al., 2019). In such a learning environment, students have difficulty in perceiving how to apply knowledge, to solve real-life global challenges, as well as lack the ability to make links between knowledge from multiple subjects (Cipková et al., 2020). For learning to be meaningful, Ausubel et al. (1968) indicate information needs to be completely conceptualized and used to make connections with other previously known knowledge, thus aiding further learning. As indicated in previous research, applying meaningful learning methods (e.g. mind mapping tasks), has a positive influence on students’ self-efficacy (Baltaoğlu & Güven, 2019). DCIs and ICIs form a unified scientific framework for various topics of the curriculum, as set out in the curriculum and are forming a necessary core for conceptualizing science (NRC, 2012; Author 1 et al., 2019). These are important in everyday life and in the future, currently agreed upon by science and society (Author 1 et al., 2019). DCIs and ICIs can support a perception of interdisciplinarity between science subjects and in so doing, support the development of conceptualizations, which, in turn, makes the learning process more meaningful (NRC, 2012). The goal of this research is to identify students’ ability to use DCIs and ICIs to form maps to support meaningful learning across science subjects. The following research questions are put forward:

RQ1 How effective are students in expanding DCI and ICI maps as a tool for promoting self-efficacy in science?

RQ2 What differences occur in students’ self-efficacy between an experimental group that expand DCI and ICI maps and a control group not utilizing such maps?

RQ3 What are students’ and teachers’ perceptions of the developed teaching/learning method, within the experimental group, for supporting students’ self-efficacy?

The student sample consisted of an experimental group (209 students, and 12 teachers, undertaking the intervention from five schools) and a control group (no intervention). The intervention was carried out in the five experimental schools for 18 months from January 2019 to June 2020 involving students from grade 10 and 11. The control groups consisted of 162 students also from five schools and were chosen according to similar characteristics (school location and number of students, teachers, etc.) as the experimental groups. Before the intervention, one teacher from each school (a total of 5) participated in a four-day (24 hours) professional development workshop. All teachers who participated in the workshop also collaborated with other science teachers for promoting science teachers’ collaboration and to bring about interdisciplinary interconnections. The selection of 10 core ideas chosen for this intervention, were published in previous research conducted by this research author and her colleagues (2021). During the intervention, the corresponding core idea maps were created by students. A pre-and post-questionnaire (Author 1 et al., 2019) was used for determining students’ self-efficacy, related to core ideas. All questions were answered using a 4-point scale ranging from 1- “I do not agree at all” to 4- “I definitely agree”. While the pre-questionnaire was administered by paper and pencil, the post-questionnaire was by using a Google Form template. This made it possible to collect data during the COVID-19 epidemic. Interviews were conducted with the experimental group students and teachers to determine their perceptions of the developed method. The interview questions were developed and validated by the researchers. Students participating in the study provided consent as required from all of the participated schools and their school heads. To analyze quantitative data gained from the questionnaire, descriptive statistics and reliability were used and conducted using SPSS version 24. The statistical program Mplus (Version7) was used for the confirmatory factor analysis (CFA). The qualitative data from interviews were analyzed descriptively following the approach proposed by Patton (1990). For in-depth analysis, the collected students’ and teachers’ answers were encoded using inductive thematic analysis as a standard content analysis.

This research sought to provide empirical evidence how the implementation of expanding disciplinary and interdisciplinary core idea maps as a method might enhance students’ perceived self-efficacy. In general, the method in which students expanded DCI and ICI maps was seen as effective and supported students’ perceived self-efficacy in Life Science, Earth Science, and with Models and Systems. Reasoning for this was that in these areas it seemed easier for students to recall what they had learned previously. But, although positive tendencies were found within Chemistry and Physics, the change in students’ perceived self-efficacy was not statistically significant. The comparison between the experimental and control group confirmed that the intervention had a positive change on students’ perceived self-efficacy towards disciplinary and interdisciplinary core ideas. The outcomes from the conducted interviews revealed that, in general, students’ and teachers’ perceptions of the developed method for supporting students’ perceived self-efficacy was positive. They felt that the DCI and ICI maps helped to support students’ meaningful learning. Both teachers and students stated in their interviews that knowledge construction tasks (knowledge visualization through mind mapping and concept mapping, handling scenarios, making interdisciplinary interconnections) helped students to better link prior knowledge to new knowledge.

Ausubel, D., P. (1968). Educational psychology: A cognitive view. New York: Holt Rinehart: NewYork. Baltaoğlu, M., G., & Güven, M. (2019). Relationship between self-efficacy, learning strategies and learning styles of teacher candidates (Anadolu University example). South African Journal of Education, 39(2), 1–11. Cipková, E., Karolcík, S., Scholzová, L. (2020). Are Secondary School Graduates Prepared for the Studies of Natural Sciences? Evaluation and Analysis of the Result of Scientific Literacy Levels Achieved by Secondary School Graduates. Research in Science & Technological Education, 38(2), 146–167. NRC (2012). Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. The National Academies Press, Washington, DC. www.nap.edu OECD (2019). PISA 2018 Results (Volume I): What Students Know and Can Do, PISA, OECD Publishing, Paris https://doi.org/10.1787/5f07c754-en Author 1, Author 2 & Author 3 (2021; 2019).