{"id":12976,"date":"2023-07-31T19:05:15","date_gmt":"2023-07-31T19:05:15","guid":{"rendered":"https:\/\/citejournal.org\/\/\/"},"modified":"2023-11-15T16:45:25","modified_gmt":"2023-11-15T16:45:25","slug":"teaching-science-via-computational-thinking-enabling-future-science-teachers-access-to-computational-thinking","status":"publish","type":"post","link":"https:\/\/citejournal.org\/volume-23\/issue-3-23\/science\/teaching-science-via-computational-thinking-enabling-future-science-teachers-access-to-computational-thinking","title":{"rendered":"Teaching Science via Computational Thinking? Enabling Future Science Teachers\u2019 Access to Computational Thinking"},"content":{"rendered":"\n
As an approach to solving problems by using computer science techniques and methods, computational thinking (CT) has been emphasized as a critical skill necessary for a society that relies on complex computer technologies (Grover & Pea, 2013; Wing, 2008). The growing importance of CT in education has also become clear in the national standards. For instance, computational thinking is included as a one of the core scientific and engineering practices in the Next Generation Science Standards<\/em> (NGSS; NGSS Lead States, 2013), while it can also be a thinking process that can support other practices (e.g., developing and using models) and help address the key cross-cutting concepts (e.g., patterns). Such an interest in integrating CT in teaching is due to the increasing computational nature of the science and mathematics fields, which are demanded for current and future workforce (e.g., bioinformatics, computational statistics, or computational neuroscience; Weintrop et al., 2016).<\/p>\n\n\n\n The growing number of educational initiatives (e.g., CS4All) that focus on coding and programming reflects the assertion that such tasks promote CT, as they may provide students with opportunities to explicitly practice CT skills (Voskoglou & Buckey, 2012). However, such efforts tend to target middle and high school in-service teachers in big cities and large school districts (Google Inc. & Gallup Inc., 2016; Guzdial, 2016), while the focus on preservice teachers (PSTs) is limited (Yadav et al., 2017). Consequently, PSTs placed in poorer and rural schools with limited technology access will likely have fewer opportunities to learn how to develop their future students\u2019 CT skills.<\/p>\n\n\n\n Thus, equitable CT opportunities in teacher education programs that work with rural placement-schools are essential, and the efforts need to take into account potential digital divide barriers to make CT more accessible to PSTs. As an initial step, the current examined how a specific workshop, designed to infuse CT in a science methods course, may influence PSTs\u2019 access to CT.<\/p>\n\n\n\n Further, the skepticism over the limited evidence that CT can transfer to other areas beyond computer science (Denning, 2017; Guzdial, 2015) highlights the potential difficulty that educators may have in relating it to pedagogy. Given the importance of understanding both content and pedagogy in successful use of any technological interventions, the ways in which PSTs\u2019 understanding of CT may be connected to their pedagogical approach are also essential to this study. As such, the second aim of the study was to examine the relationship between PSTs\u2019 exposure to the CT-infused workshop and their lesson plans designed based on the 5E Model (Bybee, 2015a), a widely accepted inquiry-based instructional model for teaching science conceptual understanding (Contant et al., 2018).<\/p>\n\n\n\n CT has been considered as an effective approach that uses computer science concepts and techniques to solve complex problems in a society that relies on complex computer technologies (Wing, 2008). The view that CT can be used to engage students consciously in making artifacts (e.g., design systems) in situated environments reflects the constructionist perspective in education (Papert & Harel, 1991). In particular, CT may start with encountering a problem, breaking it down into smaller components, identifying the patterns among them, abstracting a generic solution, generating algorithms to automate the solution, and analyzing the solution effectiveness (Barr et al., 2011; Grover & Pea, 2013; Wing, 2008), which mirror the problem-solving process, namely understanding and representing, planning, and executing and self-regulation (Mayer & Wittrock, 2006; OECD, 2003, 2015).<\/p>\n\n\n\n Although CT may be broader than just a method to solve problems, such as developing computational models for inquiring and understanding phenomena (Denning, 2017), the problem solving nature of CT has been well recognized and emphasized in the literature (e.g., Voogt et al., 2015). As such, the opportunities that engage students in the CT processes are naturally of interest to educational research and practice focusing on promoting problem solving (Kale et al., 2018). Programming, in the form of developing and executing codes to instruct computers to complete specific tasks, has specifically been viewed as an effective means enabling students to explicitly practice CT skills (Voskoglou & Buckey, 2012). Due to the recursive process of coding, students can have multiple attempts and use multiple problem elements to break down challenging tasks and to develop and test their solutions. As such, coding and programming tasks to promote students\u2019 CT may potentially engage students in the problem-solving process.<\/p>\n\n\n\n The assertion that programming tasks promote CT is also reflected in the national standards (e.g., NGSS & Common Core), the increasing number of programming classes (Google Inc. & Gallup Inc., 2016), and coding initiatives such as Digital Promise, MakerEd, and CS4All (Herold, 2017; Madda, 2016; Smith, 2016; The White House, 2017). The noticeable surge in research studies on CT also echoes the same trend. According to a recent meta-analysis of empirical papers on CT published between 2006 and 2017 (Hsu et al., 2018), coding and programming was the most focused area. Another meta-analysis focusing on CT assessment also revealed that computing and programming was the most frequently assessed subject (Tang et al., 2020). Further, visual coding programs to promote CT (e.g., block-based programs) have been shown to increase students\u2019 self-efficacy toward coding (Arslan & Isbulan, 2021), programming performance (Namli & Aybek, 2022), thinking skills (Gunbatar & Turan, 2019), and academic achievements (Hu et al., 2021).<\/p>\n\n\n\n Despite the increasing number of coding initiatives to promote CT and the efforts to emphasize critical aspects of CT, their main focus on middle and high school students (Google Inc. & Gallup Inc., 2016) is far from exemplifying opportunities for PSTs to learn how to promote CT in elementary school settings, which may be problematic for the future efforts to support students\u2019 CT. Also, while the growing number of new initiatives signals the potential spread of CT to teacher education programs, the majority of the existing efforts still focus on in-service teachers (Yadav et al., 2017).<\/p>\n\n\n\n The growing efforts in teacher education programs, on the other hand, has mostly focused on computer science concepts as a stand-alone subject while a few initiatives emphasize subject-specific CT. For instance, as part of undergraduate educational technology courses, PSTs have been provided with opportunities to practice coding to improve algorithm and debugging skills (Angeli, 2022), develop knowledge of and positive attitudes toward CT (Chan, 2021), or enhance the knowledge and disposition of CT process (Butler & Leahy, 2021; Mouza et al., 2017).<\/p>\n\n\n\n Only a few studies have aimed to increase PST\u2019s CT skills and conceptual understanding of science concepts. For example, Bati (2022) asked preservice teachers to design algorithms to solve science problems (e.g., designing a thermometer conversion that converts a temperature value from Celsius to Fahrenheit, or vice versa). In another study, preservice teachers worked on using Micro:bit (a tiny circuit board designed to introduce computing to young children) to create a simulation of the moon\u2019s phases and using Microcontroller to create a pH meter (Pewkam & Chamrat, 2022).<\/p>\n\n\n\n Nevertheless, these existing studies solely examined the impact of coding activities on PSTs\u2019 CT knowledge and understanding, while access to technology, including motivation and actual usage (which can be limited in remote schools), were not investigated. Given that existing initiatives have predominantly focused on large school districts in big cities and that remote regions have not been the center of previous efforts (Guzdial, 2016), PSTs placed in poorer and rural school districts may have limited opportunities to learn how to develop their students\u2019 CT skills. This becomes even more problematic given that rural schools tend to have limited access to advanced technology infrastructure as well as opportunities for professional development (Aduwa-Pgiegbaen & Iyamu, 2009; Palamakumbura, 2009; Trinidad, 2007; Wood & Howley, 2012).<\/p>\n\n\n\n Although unplugged activities (e.g., noncoding activities without computers) can provide effective means to support students\u2019 CT skills in rural areas with limited technology access (Yuliana et al., 2021), the plugged activities (e.g., coding) can still provide opportunities for students to make multiple attempts and use various problem elements to decode challenging tasks and to develop, test, and refine solutions. Thus, while it is essential to provide equitable CT opportunities via plugged activities in teacher education programs whose PSTs are placed in rural school settings, the efforts need to consider potential digital divide barriers.<\/p>\n\n\n\n Digital divide is not just about physical access to technologies but also related to an individual\u2019s motivation, skills, culture, and attitudes toward using information communication technology (ICT: DiMaggio & Hargittai, 2001). To better conceptualize and study the digital divide, van Dijk (2005) conceptualized an ICT access model with four distinct levels, which includes motivation, physical, skills, and usage. The first level refers to users\u2019 needs and motivation to use technologies. Next comes physical access in the form of having technologies. Skills access as the third level is about possessing skills to use technologies. Usage access, the last level, refers to the applications and usage frequency.<\/p>\n\n\n\n Van Dijk (2005) argued that unequal access at these levels would limit the degree of participation in society. Extending this theory to computational thinking, PSTs with unequal access levels would likely have limited participation in efforts to learn and teach CT and, consequently, be less likely to help develop the CT skills of the future workforce. While teacher education programs should be integral to helping PSTs\u2019 preparation in this aspect, the ways specific course activities can, in fact, impact PSTs\u2019 CT access have yet to be examined. As a preliminary step, the current study examined how a specific workshop, designed to infuse CT in a science methods course, influenced PSTs\u2019 motivation, skill, and usage access to CT and CT tools. The specific research questions within this research focus included the following:<\/p>\n\n\n\n Despite the potential of CT as a problem-solving approach in education, the skepticism over its ambiguous definition and the limited evidence that it can transfer to other areas beyond computer science (Denning, 2017; Guzdial, 2015) raise possible challenges for educators regarding understanding and using it as part of their pedagogy. Because a successful integration of technological innovations in teaching requires not only the understanding of the technology but also the content-specific pedagogical knowledge (Mishra & Koehler 2006), how PSTs\u2019 understanding of CT may be connected to their pedagogical approach in teaching is, thus, essential to study as well.<\/p>\n\n\n\n For the past decade, the development of the NGSS (NGSS Lead States, 2013) has prompted challenging shifts for teaching science that have aimed not only to support student learning of disciplinary core ideas but also to engage them in scientific and engineering practices and to help develop an understanding of concepts across different domains of science. Regarding teacher education programs responding to such shifts, one recommended key strategy is to involve preservice teachers in full inquiries where they can develop science and engineering practices via data collection, analysis, explanation, and communication (Bybee, 2014). One of the ways to provide preservice teachers with such inquiry-based teaching and learning opportunities is the use of the 5E Model (Bybee, 2015b), a widely accepted inquiry-based instructional model for teaching science conceptual understanding (Contant et al., 2018), which has also been extensively researched in teacher education (Kazempour et al., 2020).<\/p>\n\n\n\n Building on the Learning Cycle, an earlier inquiry-based model, the 5E Model emphasizes five distinct phases of learning \u2013 Engage, Explore, Explain, Elaborate, and Evaluate (Bybee, 2015a). The focus of the Engage phase is to promote students\u2019 curiosity about and interest in the topic while helping them make connections to what they already know about it. Regarding CT, this phase may provide the problem of interest, which would be decomposed for enhanced understanding of the problem. During the Explore phase, students are given opportunities to design and conduct investigations about the topic while they are guided to explain and share their understanding from such experiences in the Explain phase. The Explore phase may be conducive to data practices of CT (Weintrop et al., 2016), while the Explain phase may be ideal for engaging students in recognizing patterns as part of data analysis. <\/p>\n\n\n\n Students also broaden their newly gained understanding by applying it to new issues or aspects of the topic in the Elaborate phase. Because the Elaborate phase is ideal for encouraging interaction with further sources, including web-based simulations (Bybee, 2015b), students may also engage in the modeling and simulation practices of CT (Weintrop et al., 2016) in this phase. During Evaluation, which can occur concurrently with any previous phases, students are engaged in self-evaluation while teachers monitor their progress and assess their understanding. Regarding CT, students\u2019 efforts in debugging the encountered problems and analyzing their solutions may provide self-evaluation opportunities. <\/p>\n\n\n\n Although the 5E Model can enhance PSTs\u2019 understanding of the inquiry-based instruction (Hanuscin & Lee, 2008) and certain phases may be conducive to supporting CT processes and practices, only a few studies and examples have explicitly described CT in lessons designed based on the 5E Model. For instance, a piloted lesson in a secondary school setting involved the use of physical computing (Arduino software and a pulse sensor) to measure a heartbeat and plot it via a spreadsheet program during the Explore phase (Newland & Wong, 2022).<\/p>\n\n\n\n Another example in an elementary school setting (Nolting et al., 2021), focusing on placing objects in the path of a beam of light, engaged students in a plugged activity (e.g., navigating a physical maze layout on ground made of different colored fabric sheets) during the Explore phase and in an unplugged activity (e.g., programming a puzzle game where a bot moves to different locations that light up).<\/p>\n\n\n\n While such uses of the 5E model have been reported to benefit students\u2019 mastery of CT skills and concepts (Gao & Hew, 2022), CT processes (e.g., automation) exemplified in in-service teachers\u2019 lessons based on the 5E Model were yet to be sufficient (Mumcu et al., 2023). Further, in-service teachers\u2019 challenges, such as limited computer science and programming knowledge and the difficulty in keeping students focused on the computer science tasks (Yadav et al., 2016), may even be more problematic for future teachers who have a limited teaching repertoire.<\/p>\n\n\n\n As such, the ways PSTs connect their newly gained understanding of CT with the 5E Model needs to be explored. As an initial step, the current study aimed to examine the relationship between PSTs\u2019 exposure to the CT-infused workshop and their lesson plans. As described in the Methods section later, the participating PSTs in the current study developed lesson plans according to the 5E Model throughout the semester and then were asked to modify the plans based on their experiences with and understanding from the workshop provided. The specific research questions, in this regard, include the following:<\/p>\n\n\n\n Participants included all of the 3rd<\/sup>-year PSTs (N<\/em> = 43) from the two sections of an elementary education science method course (taught by the first and second authors) in a teacher education program at a mid-Atlantic university in a largely rural state nestled in the Appalachian Mountains. The two intact classroom sections were randomly assigned to either a control group or an experimental group. The experimental group attended a CT-infused workshop. There were 23 participants in the control group and 20 in the CT-infused group.<\/p>\n\n\n\n The course introduced the PSTs to the teaching and learning of elementary school science through in-class activities that were designed to help them unpack the NGSS, analyze student thinking, revise and teach an existing science lesson in their placement schools, and design and modify a full science lesson unit based on the 5E Model. The PSTs spent around 17 hours per week in their placement classrooms during the semester.<\/p>\n\n\n\n The research study was guided by a pre- and posttest quasi-experimental design (Creswell, 2003). At the beginning of the semester, the PSTs were introduced to the study. Those who agreed to participate completed an online presurvey, which took approximately 20 minutes on average. During the semester, they completed various course activities, which are described in a subsequent section. The link to the postsurvey with the same questions was emailed to the PSTs at the end of the semester (see the Data section for the details about the survey questions).<\/p>\n\n\n\n The course activities that participants in both the control and the CT-infused groups completed included (a) attending the weekly class sessions, (b) conducting an interview with a student from placement classroom to assess children\u2019s ideas and thinking about scientific phenomena, (c) revising, teaching, and reflecting on an existing science lesson plan, (d) attending a few workshops offered by guest speakers on digital technologies (DigTech), garden-based learning (GBL), and water resource education (Water), (e) developing a cohesive lesson unit that contains the five phases of a learning cycle (Engage, Explore, Explain, Elaborate, and Evaluate), (f) modifying the 5E lesson unit based on any of the workshops attended, and (g) practicing the phases of the 5E Model by conducting simple experiments on water movement in plants.<\/p>\n\n\n\n Besides the additional workshop sessions on CT, all the classroom activities were kept the same for both sections of the course. The two sections were taught by two instructors who met on a weekly basis to discuss and plan each week\u2019s lesson. For all of the in-class sessions, the instructors used the same lesson plans. They provided the PSTs with the same instructions and examples regarding completing each of the course assignments (Items b, c, e, f, and g in the prior paragraph).<\/p>\n\n\n\n All of the workshop sessions except for the one focusing on CT (see next section) were offered by the same guest speakers, who had provided the sessions in the previous year. Also, while the PSTs could interact with those in the other section outside the class time, it would be unlikely for the treatment group to digest the content of the CT workshop, without accessing and carefully reviewing the workshop files, practicing coding, modifying the sample projects, and discussing the lesson ideas.<\/p>\n\n\n\n In addition to completing the activities described in the previous section, the PSTs in the treatment group participated in two more workshop sessions that focused on integrating CT activities in teaching science. Each session was offered by the first author and lasted 75 minutes over 2 weeks. Table 1 outlines the scope of the additional workshop activities for the treatment group as well as the activities completed by all PSTs:<\/p>\n\n\n\n Table 1<\/strong>Literature<\/h2>\n\n\n\n
CT to Problem Solving<\/h3>\n\n\n\n
Coding to Think Computationally<\/h3>\n\n\n\n
CT in Teacher Education<\/h3>\n\n\n\n
Information Communication Technology Access<\/h3>\n\n\n\n
\n
Science Pedagogy for PSTs<\/h3>\n\n\n\n
\n
Methods<\/h2>\n\n\n\n
Participants<\/h3>\n\n\n\n
Research Design<\/h3>\n\n\n\n
Class Activities for All Students<\/h3>\n\n\n\n
CT-Infused Workshop for the Treatment Group<\/h3>\n\n\n\n
Course Activities for Participants<\/em><\/p>\n\n\n\n