27. Didactics - Learning and Teaching
Paper
Technology In a Inclusive Learning Environment with Room for All
Atle Kristensen1, Bente Forsbakk2
1Nord universitet, Norway; 2Nord universitet, Norway
Presenting Author: Kristensen, Atle;
Forsbakk, Bente
McLoughlin & Lee (2008) describe that in a society, which is increasingly adopting a variety of high-speed technologies, students have access to a variety of resources, ideas and communities to support their learning environment. In order for individuals to participate and engage in democracy and citizenship, they should be able to use relevant digital tools (UtdanningsdirektoratetNorwegian Directorate for Education and Training, 2017). To allow students to become active and engaged in their own learning, teachers need to understand how technology can support communication, creativity and innovation. In addition, teachers need to be aware of the opportunities, limitations, effects and risks of using technology (European Commission, 2019). Students digital competence is expressed as knowledge, skills and attitudes through coincident technology in school and in leisure time (Vuorikari et al., 2022).
In teacher's selection of learning resources, an understanding of technology as part of the students' learning environment should be based on the same understanding of how digital technology can add value to the students' learning. Kolb (2017) refers to three main reasons for adopting digital technology. Technology must engage and help students stay focused on tasks or activities. Furthermore, technology can contribute to increased motivation and learning outcomes. By changing view from passive receiving to active contributing in their own learning, Technology also give students opportunities to learn in new ways beyond their typical school life through changing their role from passive receiver to active contributors in their own learning. Learning with technology does not happen because a particular tool, or application, revolutionizes education, but when teaching and learning are connected to technology.
Through the lens of The Tree P's of pedagogy for the Networked society (McLaughlin & Lee, 2008), students’ learning is driven by personal needs, ability to collaborate with others, and active participation in their own learning. More engaging, socially based learning is needed to replace the traditional classrooms, which emphasize the institution and the instructor. Customized learning refers to the idea that learning should be tailored to each student's individual needs, interests, and abilities. This can be achieved by selected use of technology, which can adjust the content and pace of learning, based on the student's prerequisites, gender, cultural and linguistic affiliation. Overall, there are a plethora of learning resources that support user autonomy, increased levels of socialization, interactivity, and creativity. Different resources provide access to open communities and peer-to-peer networks to move beyond instructor-centered classroom environments. This is in contrast to prescribed curricula and content that are often restricted through learning management systems.
Norwegian municipalities report that they encounter a jungle of digital learning resources, which is largely based on analog formats, from both national and international providers. 36 % of schools in Norway lack a systematic plan for competence enhancement in digital competence (Kunnskapsdepartemenet, 2020). The emergence of digital learning resources has made access to learning materials unclear and challenging for the teacher when choosing and using technology in the students' learning environment. Without expertise and competence on what is to be purchased, the purchases risk becoming random (Kunnskapsdepartemenet, 2020).
The challenge for teachers is therefore judging the quality and choosing appropriate technology. The teacher should have knowledge of how technology changes and expands the subject's content, the pedagogical methods and have an overview of how technology can add value in the students' learning environment (Koehler & Mishra, 2014).
The study has the following research question: What do teachers emphasise when choosing digital learning resources in a learning environment with room for all students?
The issue is operationalized into three areas:
- the teacher's awareness of digital learning resources based on the students' learning assumptions and resources (individualization)
- gender
- cultural and linguistic affiliation.
Methodology, Methods, Research Instruments or Sources UsedThis qualitative interview study is designed in the understanding that knowledge is a social construct created between people. Through language, a representation of reality is created, a socially constructed representation (Wadel & Wadel, 2007). Understanding and knowledge is developed in an interaction between researchers and teachers in the interview situation. Thus, this study is placed within the social constructionist tradition, where knowledge, and all meaningful reality, is based on interactions between people in a context (Crotty, 1998). The study is inspired by a phenomenological starting point where we as researchers are concerned with issues and delimitations. The emergence of teachers' descriptions will primarily provide experiential material that is rich and detailed (Van Manen, 2014, p. 316).
Through interviews with experienced teachers, we seek knowledge and understanding of teachers' selection of digital learning resources for the students' learning environment. The study follows guidelines for research ethics and has been approved by NSD (Norsk senter for forskningsdata). Through question triggers (Krumsvik, 2014) based on topics from our theoretical framework, an interview guide was designed and semi-structured research interviews planned to be conducted (Postholm & Jacobsen, 2018). In interviews, teachers will have the opportunity to refer to their own experiences through retrospective descriptions of experiences and opinions related to these (Giorgi, 1985).
The order of topics and questions in a semi-structured interview may vary from interview to interview (Johannessen, et.al., 2016), which is also common in the semi-structured interview. The interviews are therefore intended in an informal style so that the informants can supplement with their own input (Krumsvik, 2014). In this way, we move back and forth in the interview guide to get answers to the questions "what" and "how"; what is experienced in consciousness, and how or under what conditions, is the phenomenon or event experienced (Van Manen, 2014).
In the analysis of the empirical data, we are using Kolb (2017)'s Triple E model. Our empirical data will be coded and thematized in meaningful findings on the basis of this framework.
Conclusions, Expected Outcomes or FindingsExpected outcomes/results
Results of the study are expected to be concentrated on developing knowledge about three main areas:
1) Knowledge of teachers' choice of digital learning resources based on principles related to differentiated instruction. In particular, we expect the study to construct knowledge about teachers' conscious choices related to the individual pupil's aptitudes for learning through personalization.
2) Knowledge of teachers' selection of digital resources to create a flexible, personal and inclusive learning environment when technology is adopted. Students have different needs and teachers can meet the needs of all students and provide differentiated instruction by using different digital learning resources that take into account the students' gender, cultural and linguistic affiliation.
3) Knowledge of teachers' awareness of digital resources that can create activity and creativity in flexible learning groups based on students' needs and interests.
Descriptions from teachers through semi-structured interviews are assumed to provide insight and knowledge about different qualities within the chosen areas of study. It is assumed that the study will be able to provide sufficient results from the empirical material based on interpretations in light of the theoretical framework from Kolb (2017) and McLaughlin & Lee (2008).
ReferencesReferences
European Commission (2019). Key competences for lifelong learning. Publications Office of
the European Union. https://data.europa.eu/doi/10.2766/569540
Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. SAGE
Giorgi, A. (1985). Phenomenology and psychological research: essays. Duquesne University Press.
Johannessen, A., Christoffersen, L. & Tufte, P. A. (2016). Introduksjon til samfunnsvitenskapelig metode (5. utg.). Abstrakt.
Koehler, M. J. & Mishra, P. (2014). The Technological Pedagogical
Knowledge Framework. I J. M. Spector (Red.), Handbook of Research on Educational Communications and Technology (s. 101-111). Springer. https://www.punyamishra.com/wp-content/uploads/2013/08/TPACK-handbookchapter-2013.pdf
Kolb, L. (2017). Learning First, Technology Second: The Educator's Guide to Designing Authentic Lessons. International Society for Technology in Education.
Krumsvik, R. J. (2014). Forskningsdesign & kvalitativ metode -en introduksjon. Fagbokforlaget.
Kunnskapsdepartementet (2020). Handlingsplan for digitalisering i grunnopplæringen (2020-2021). https://www.regjeringen.no/contentassets/44b8b3234a124bb28f0a5a22e2ac197a/handlingsplan-for-digitalisering-i-grunnopplaringen-2020-2021.pdf
McLoughlin, C. & Lee, M. J. W. (2008). The Tree P’s of pedagogy for the Networked society: Personalization, participation and productivity. International Journal of Teaching and Learning in Higher Education, 20, 10-27. https://www.researchgate.net/publication/284125788_The_three_P's_of_pedagogy_for_the_networked_society_Personalization_participation_and_productivity
Postholm, M. B. & Jacobsen, D. I. (2018). Forskningsmetoder for masterstudenter i lærerutdanningen. Cappelen Damm akademisk.
Utdanningsdirektoratet Norwegian Directorate for Education and Training (2017). Overordnet del – verdier og prinsipper for grunnopplæringen. https://www.udir.no/lk20/overordnet-del/?lang=nob
Van Manen, M. (2014). Fenomenologi av praksis: meningsgivende metoder i fenomenologisk forskning og skriving. Left Coast Press.
Vuorikari, R., Kluzer, S. & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for citizens - With new examples of knowledge, skills and attitudes. Publications Office of the European Union. doi:10.2760/490274
Wadel, C. C. & Wadel C. (2007) Den samfunnsvitenskapelige konstruksjonen av virkeligheten. Cappelen Damm.
27. Didactics - Learning and Teaching
Paper
Aesthetic Experience in Technology Education – A Case Study of Robotic Programming
Maria Andrée1, Per Anderhag1, Sebastian Björnhammer1, Niklas Salomonsson2
1Department of Teaching and Learning, Stockholm university, Sweden; 2Education and Administration, City of Stockholm, Sweden
Presenting Author: Andrée, Maria;
Anderhag, Per
This study focuses on the aesthetic dimensions of the learning of technology; taking the stance that the doing of technology - in and out of schools - is inseparable from aesthetic experiences. In technology education, aesthetics has been emphasized as foundational to design and appreciation of aesthetical qualities in technological artifacts related to personal identity and lifestyle (DeVries, 2016). Previous research has however primarily attended to aesthetics in technology education in terms of student attitudes and motivation towards different aspects of the technology subject based on student reports in surveys (Potvin & Hasni, 2014). The studies are usually motivated by the important relation between student interest and learning (del Olmo-Muñoz et al., 2021; Witherspoon et al., 2016), observed gender differences in attitudes (Virtanen et al., 2015), the need of a qualified workforce and societies need of technological literate citizens (Ardies et al., 2015). Since most of previous research on student attitudes builds on Likert-type questionnaires, such as the PATT-survey, the knowledge of the role of aesthetics and taste for student learning technology is largely based on students’ recollections of their experiences of technology class. To our knowledge, only rarely have attitudes and identity work been contextualized as situated and so describing aesthetic experiences as constituted in classroom action. What role aesthetics has for student learning and identity work in technology class is thus little investigated. The aim of the study is therefore to explore aesthetics and technology education, and more specifically we ask: What role has aesthetics for learning when students are programming robots in technology class? The study thus focuses on programming activities where aesthetic experiences are not so much related to exterior design features but more with the processes designing functional programming solutions. In the Swedish technology syllabus, programming is part of the core content methods for developing technological solutions and in years 1-3 (age 7-9) the students are supposed to learn to control objects, such as a robot, using programming. In years 4-6 (age 10-12) the students should learn to control their own constructions or other objects by using programming, and in years 7-9 (age 13-15), the students are supposed to use programming for controlling and regulating their own constructions. Programming is thus primarily a tool for controlling objects and a progression in terms of knowledge in programming is not formulated in the technology syllabus.
The study is grounded in a pragmatic and anti-representational perspective on meaning-making (eg. Kelly et al., 2012), words and actions are thus not understood as ready-made once for all but rather approached as gaining their meaning through their use and consequences as part of activities. Here we primarily draw on previous studies within the pragmatic perspective that have approached the teaching and learning of a school subject as constituting a process in which cognition, norms and values (aesthetics) are intertwined (eg. Wickman, 2006)
Methodology, Methods, Research Instruments or Sources UsedThe data for the study comes from two lower secondary technology classrooms in Stockholm, Sweden. One of the authors was the teacher of one of the student groups participating. The students (year 9, ages 15-16) were working with a task of pair-programming Lego robots that should perform specified movements, such as following a curved line. Every group screen recorded while they were coding which resulted in films showing how the program gradually emerged. This in situ programming activity and associated student talk constitutes the data of the study. In total 7 screen recorded films, 4 from School A and 3 from school B, were transcribed verbatim and analyzed. The length of the films varied from 30 to 60 minutes. The transcribed films were initially analyzed to identify aesthetic situations, primarily evident when students made taste distinctions (Author et al., 2015) and aesthetic evaluations while they were programming. These situations were categorized and further analyzed using Practical Epistemological Analysis (PEA) (Wickman & Östman, 2002). PEA is grounded in a situated perspective on meaning making and learning is operationalized as discourse change as part of an activity (Kelly et al., 2012). We primarily used three of the analytical concepts of PEA, stand fast, gap and relation, to identify the role of aesthetics for student learning. Relations are established by the participants in an activity between the words and action that make sense, that is stand fast, in the situation and what is not. Analytically, this is described as the participants establishing a relation to fill a gap. A gap is evident in student talk and actions as they ask questions or acknowledge that there is something that they do not understand, such as for example what a loop is or why the use of a loop may solve a certain coding dilemma. Here we are primarily interested in situations where taste distinctions and/or aesthetic judgements are used by the students and the teachers to acknowledge or fill gaps.
Conclusions, Expected Outcomes or FindingsThe results show that aesthetics contribute to student learning in several ways, for example were aesthetic judgements used by the students and their teacher for evaluating distinctions on ways to proceed and so orienting learning towards the purpose of the activity. The students and their teacher negotiated and aesthetically evaluated norms concerning what constitutes functional code but also ways-to-be to be in the programming activity. The aesthetic language thus played an important part in socialization and how the students would position themselves as programmers or as non-programmers. Throughout the activity, expectations and evaluations of the code's construction and the robot's behavior became visible through students' expressions of frustration, anger, resignation, laughter, joy, and humor. An interesting finding was that student talk and doings revolved around the construction of the code in terms of its functionality. This became evident when the students executed their programs and used aesthetic expressions evaluating the extent to which the robot behaved as anticipated. Through aesthetic expressions, the students thus continuously evaluated the functionality of their programs (did the codes do what was intended, i.e. moving the robot in a specific way). Our findings contribute to the understanding of aesthetic experiences in technology education as contributing to the processes of learning and meaning-making and not only connected to design features of the artifacts produced.
ReferencesAuthor et al., 2015
Ardies, J., De Maeyer, S., Gijbels, D., & van Keulen, H. (2015). Students attitudes towards technology. International Journal of Technology and Design Education, 25, 43–65
del Olmo-Muñoz, J., Cózar-Gutiérrez, R. & González-Calero, J.A. (2022). Promoting second
graders’ attitudes towards technology through computational thinking instruction. International Journal of Technology and Design Education, 32, 2019–2037
Kelly, G. J., McDonald, S., & Wickman, P.-O. (2012). Science learning and epistemology. In K. Tobin, B. J. Fraser & C. J. McRobbie (Eds.), Second International Handbook of Science Education (pp. 281–291). Dordrecht: Springer Netherlands.
Potvin, P., & Hasni, A. (2014). Interest, motivation and attitude towards science and technology at
K-12 levels: a systematic review of 12 years of educational research. Studies in Science Education, 50(1), 85-129.
Virtanen, S., Räikkönen, E. & Ikonen, P. (2015). Gender-based motivational differences in
technology education. International Journal of Technology and Design Education, 25,197–211
Vries, M.J. de (2016). Teaching about Technology an Introduction to the Philosophy of Technology
for Non-philosophers. (2nd ed. 2016.) Cham: Springer International Publishing.
Wickman, P.-O. (2006). Aesthetic experience in science education: learning and meaning-making as
situated talk and action. Mahwah, N.J.: Lawrence Erlbaum Associates.
Wickman, P.-O. & Östman, L. (2002). Learning as discourse change: A sociocultural mechanism.
Science Education, 86, 601-623.
Witherspoon, E.B., Schunn, C.D., Higashi, R.M. & Baehr, E.C. (2016). Gender, interest, and prior
experience shape opportunities to learn programming in robotics competitions. International Journal of STEM Education, 3, 18, 1-12
27. Didactics - Learning and Teaching
Paper
Developing Student’s Skills in Creating Technological Start-Up Projects Based on the Thinking Design Algorithm.
Ibaly Toktamyssova1, Laura Bekeshova1, Damir Yerkmaliev2
1Aktau NIS, Kazakhstan; 2Almaty NIS, Kazakhstan
Presenting Author: Toktamyssova, Ibaly;
Bekeshova, Laura
The main purpose of the study is to teach high school students how to prepare their Start-Up projects in accordance with modern requirements. Through the design thinking algorithm, you can develop the skills of preparing a startup project. In the empathy stage, teams were formed among the students, in the analysis and synthesis section, each team identified a problem that needs to be solved in the future, and in the third stage of design thinking, each group identified ways to solve the problem and started preparing a prototype (MVP). During the tests of the created prototype, the teams were able to find a timely solution to the identified obstacles. And in the last stage, each startup team presented their products at a fair held inside the school and received feedback from the audience. As a result, each team participates in various competitions and presents its products in the direction of a business idea.
The main goal of the research work is to use the thinking design algorithm to guide students in grades 9-11 to develop technological startup projects, identify the obstacles encountered and offer solutions.
Research questions:
- What do startup projects teach students in grades 9-11?
- What are the obstacles to improving the project and what actions have been taken to eliminate them?
- What is the effectiveness of the thinking design algorithm in developing technological startup projects for students?
In order not to lose motivation and interest in learning, it is important for teachers not only to conduct interesting lessons, but also to lead them to research projects. In order to implement modern business ideas, students ' desire to engage in startup projects is developing rapidly. In the process of developing startup projects, students develop skills of communicative, constructive thinking, problem solving through the accumulation and analysis of information. Therefore, in this study, an algorithm for thinking design was selected to train students to engage in startup work. D. Kelly states that thinking design relies on the natural ability to be intuitive, find patterns, and come up with ideas that are not only emotionally attractive but functional, so thinking design is an effective tool for developing creativity and skill [1]. The design of thinking is based on the ability of a person to feel intuitively, to create ideas that have not only a functional, but also an emotional component [2]. Thinking design is good for everyone because it goes beyond simple things, stereotypes, and patterns to solve and, as a result, helps open up new paths, opportunities [3]. Using 6 stages of the thinking design algorithm in the development of technological startup projects, you can hone students ' love for the complex and creative skills.
Methods of startup development. A startup is a way to test new product ideas with real customers and constantly adjust the business model to get started. In 2011, Eric Rees proposed the Lean Startup approach in his book business from scratch [4].
Methodology, Methods, Research Instruments or Sources UsedThree startup teams of three students participated in this research work with different topics. One group studied and prepared their technology startup project for two years, the other two groups developed it for a year and presented the results to competitions of different levels. Three research methods were selected for this study: interviewing students, monitoring the process of creating a startup project, and analyzing the rational and irrational aspects of each group's project [5]. The questions of interviews with students were aimed at obtaining information about the rational points of the thinking design method in the preparation of students ' startup projects and the difficulties that occurred during the process and their solution. And the development of students ' technological startup projects was controlled using a thought design algorithm. It was based on interviewing members of the group and analyzing the project, developing students ' critical thinking skills, communication skills, and information collection and analysis found in startup projects. The development of these skills was aimed at students ' positive results in competitions using the thought design algorithm selected during the analysis of the study. During the project control, the difficulties identified in testing the prototype (MVP) at the sixth stage of thinking design were analyzed and the rational aspects of the project were proposed solutions to the difficulties [6]. These selected methods can be used at the beginning of the process of preparing startup projects, in the middle, and in the final sections of the study to achieve results, helping to assess the growth of students ' research skills.
Conclusions, Expected Outcomes or FindingsAt the initial stage of empathy, students ' shared interests in the field of technology were identified and teams were formed depending on the project directions. Since it is important to identify the problem, as Williamson said in his 2015 study of starting and running start-up projects, as a result of Interview Questions aimed at identifying the problems, the consistency of the preparatory process of students in the design of the project, ways to make improvements to the project through the analysis of new information, and the strengthening of a cooperative environment between students were identified as rational points of this method [7]. Research environment in the process of monitoring the team activities of students, the third stage of thought design was the presentation of ideas aimed at solving the problem by team members. In an interview, students noted that with the help of an algorithm of thinking design, students were rational in identifying the problem that motivated their business ideas, determining the consistency and role of each team member in proposing solutions, and contributing to the formation of a system in dealing with research. At the stage of prototyping, we distributed tasks according to the abilities of each student and monitored the timely completion of the work. During the testing of the created prototype, problems were identified in each team, for example, in the startup project "Blind Klavish" for blind people, created by a team of 11th grade students, the size of the prototype was too large to cause problems in use. We decided to reduce the size of the keyboard by conducting an analysis. At the final stage of thought design, students used their communication skills to defend their projects, defended them in a limited time, and each group achieved the desired result.
References1.Kelly, D. (2015). Creative confidence.: How to release and realize your creative powers. ABC-Atticus, 278-282.
2.Goldman, S., & Zielezinski, M. B. (2016). Teaching with design thinking: Developing new vision and approaches to twenty-first century learning. Connecting science and engineering education practices in meaningful ways: Building bridges, 237-262.
3.Kashitsyn, A. S., Belov, S. V., & Bezmenov, A. A. (2013). Development of students' research skills in physics lessons. Bulletin of the Nizhny Novgorod University. NEITHER Lobachevsky, (5-2), 76-80.
4.Ros, B. (2017). The Habit of achieving: How to apply design thinking to achieve goals that seemed impossible to you. "Mann, Ivanov and Ferber", 188.
5.Ris, E. (2014). Business from Scratch: A Lean Startup method for quickly testing ideas and choosing a business model. Alpina Publisher, 45-54.
6.Wilson, J. R., & Pritsker, A. A. B. (1978). A survey of research on the simulation startup problem. Simulation, 31(2), 55-58.
7.Williamson, B. (2018). Silicon startup schools: Technocracy, algorithmic imaginaries and venture philanthropy in corporate education reform. Critical studies in education, 59(2), 218-236.
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