A critical analysis of Computational Thinking (Whakaaro Hangarau), Computer Science (Mātai Rorohiko) and Computer Programming (Papatonotanga) Digital Technology (Hangarau Matihiko) in New Zealand schools.

A dissertation by Marc Williams for the degree of Master of Education, University of Auckland  2022

CHAPTER 5 - TEACHING COMPUTATIONAL THINKING AND COMPUTER SCIENCE

5.1 Challenges and Opportunities

        There is an international prevalence of Computational Thinking and Computer Science in compulsory education however in many cases teachers are ill prepared to teach these subjects (Harris, 2018).

 

Successful Computational Thinking integration in compulsory education faces unresolved issues and challenges (Bocconi et al., 2016). There is a mixed consensus over definitions of Computational Thinking (García-Peñalvo & Mendes, 2018), preconceived notions of computing that are difficult to overcome (Lamprou & Repenning, 2018), teachers have misconceptions with the complexity of terminology (Duncan et al., 2017), teachers are reluctant to teach it (Munasinghe et al., 2021), diversity of technical words, computer jargon, metaphors and phrases in different contexts can make their meanings confusing, ambiguous or misunderstood (Munasinghe et al., 2021), teachers are ill prepared to teach the subject and there is little best practice research for teacher professional development or allocated school time for professional development and a lack of teacher confidence and competence regarding Computer Science could harm student attitudes towards the subject later (Harris, 2018)

The effectiveness of teaching Computational Thinking has been underexplored, preventing efforts to cross the large gap between early adopters and the early majority, conceptualised as the Computer Science Education chasm (Lamprou & Repenning, 2018)

Issues associated with integrating Computational Thinking into existing already congested timetables can be mitigated by incorporating Computational Thinking into Mathematics curriculums because “computational modelling is an effective approach for learning challenging science and maths concepts (Hambrusch, Hoffmann, Korb, Haugan, & Hosking, 2009). “Imaginative programming is the most crucial element of computing because it closely aligns mathematics with computing and, in this way, brings mathematics to life(Felleisen & Krishnamurthi, 2009; García-Peñalvo & Mendes, 2018).


Challenges in teaching Computational Thinking extend to different interpretations of the terms, variety and complexity of teaching resources and approaches available to students in the classroom including “semantics rather the syntax of a specific language, those that prefer some kind of programming environment based on blocks such as Scratch or based on most traditional coding languages, those that control robots or those that build physical kits to control things(García-Peñalvo & Mendes, 2018).

The international challenge in teaching Computational Thinking and Computer Science is the scope of support required to prepare teachers to teach these subjects, examples of which extends to more than 2 million primary teachers and 2.5 million secondary teachers in 28 EU countries (European Coding Initiative, n.d.), 60,000 primary school teachers in South Korea, 14,000 secondary school ICT teachers and 200,000 primary school teachers in England (Bocconi et al., 2016)

 

Switzerland’s Lehrplan21 national curriculum includes a mandatory Computer Science Education course that includes basic understanding of Computer Programming that pre-service primary school teachers must pass. The data from this initiative suggest that “it is possible to teach programming to pre-service primary school teachers however, it is less clear how much or what kind of Computational Thinking is conveyed, here appears to be preconceived notions of computing that are difficult to overcome and that though Computational Thinking has close connections to programming the first cannot be automatically learned through teaching the latter(Lamprou & Repenning, 2018)

These observations from Switzerland are reinforced by similar results from pilot studies with primary school students in New Zealand; “We had hoped that Computational Thinking skills would be taught indirectly by teaching programming and other topics in computing, but from our initial observations this may not be the case(Lamprou & Repenning, 2018). Similar studies of the perception of Computer Programming skills suggests that pre-service teachers think that they successfully learned how to program but it is less clear what they actually learnt with respect to Computational Thinking. The disparity between teaching Computer Programming and testing Computational Thinking is consistent with findings (Chapple, 1992).

5.2 Strategies

 

There are a multiverse of pedagogical strategies and learning resources to teach and learn Computational Thinking and Computer Science. Hsu et al’s studies identified Project-based learning, Problem-based learning, Co-operative learning and Game-based learning as the most prevalent strategies in Computational Thinking learning activities. “Aesthetic experience, Design-based learning and Storytelling have been relatively less frequently adopted. Future research should attempt to introduce different learning strategies, including the Scaffolding Learning Strategy, Storytelling Learning, and Aesthetic Experience, so as to aid students in multiple ways in terms of the development of subjects or high-level ability training, say, training in critical thinking and problem-solving ability” (T.-C. Hsu et al., 2018).

 

Accepted strategies to teach and learn Computational Thinking and Computer Science include using Bebras, Code.org and CS Unplugged.


Bebras Computing Challenge is an initiative by Bebras.org (Bebras.org, 2022a) that supports teachers and students learning Computational Thinking in more than 30 countries (Bebras.org, 2022b, 2022a). This construct of gamification learning enables students from ages 6 to 18 to develop their computational and logical thinking skills by answering 15 multichoice questions in 45 minutes across easy, medium and hard difficulty levels with results compared against other schools and countries.

Code.org (Code.org, 2022a) is an established global Computer Science initiative that more than 2 million teachers and 60 million students (Code.org, 2022b), 10% of all students in the world (Bučková & Dostál, 2017), have participated in and offers teacher professional development Computer Science resources from primary to secondary school level (Code.org, 2022a, 2022c). One of the Code.org strategies for teaching include the ‘Hour of Code’ activities designed for all ages and accessed in over 180 countries and 45 languages including Te Reo Māori in Minecraft (Alfriston College, 2022). There are more than 1500 scholarly articles that reference Code.org as a positive platform for learning Computational Thinking and Computer Science (Google Scholar, 2022).  


CS Unplugged (University of Canterbury, 2022b) is a free ‘Computer Science without a computer’ educational platform designed for primary to secondary students that uses printable paper based games, puzzles and other hands-on resources to learn about the principles of Computational Thinking and Computer Science without using computers.

Students use their decomposition skills to break down simple non-computerised tasks into precise, unambiguous, step-by-step instructions (algorithmic thinking), identify any errors and correct them (simple debugging)(Bell et al., 2009).

CS Unplugged was developed in the early 1990’s by Professor Tim Bell (Computer Science Educational Research Group of Canterbury University, New Zealand) (University of Canterbury, 2022b), Professor Michael Fellows (Elite Professor of Computer Science at University of Bergen, Norway) (Fellows, 2022) and Ian Witten (University of Waikato, 2022b).

CS Unplugged has widespread adoption internationally and has substantial industry support (Bell et al., 2009).

The CS Unplugged resources book, freely downloadable from the Internet (University of Canterbury, 2022c), has been translated into more than 20 languages including Arabic, Chinese, France, German, Italian, Japanese, Korean and Spanish by the international community of CS Unplugged ambassadors and students.

 

Academic research literature overwhelmingly supports the instructionally effective use of CS Unplugged to learn Computational Thinking and Computer Science without a computer. 

Unplugged computing makes Computer Science more accessible. Teachers can integrate these activities in their classrooms to teach Computational Thinking skills as they do not require any prerequisite technical knowledge(Delal & Oner, 2020).

It is recommended for school teachers teaching basic programming and Computational Thinking to consider using this offline, engaging and cost-effective approach as an alternative to computer-based methods of programming(Threekunprapa & Yasri, 2020). “Recommendation is to adopt an analog-first approach to elementary Computer Science instruction based on Computational Thinking and implemented through the framework of cognitive acceleration(Harris, 2018). “With the huge success of CS Unplugged worldwide, Bell & Vahrenhold, (2018) pointed out that it should be referred to as a general pedagogical approach and not be intended as a curriculum or a program of study and offers several benefits such as; No prerequisites for learning programming, Pedagogy offers spiral curriculum meaning, students first learn about basic facts of a subject or a topic and as the learning progresses more details are introduced, Tackling misconceptions about Computer Science in general including ‘how Computer Science is not just about programming’, and Easy deployment of activities, as no computers are required, hence, no technical issues(Arora, 2019; Bell & Vahrenhold, 2018). “Teachers have found it empowering: they already know how to work with cards, string and chalk, and how to teach young children, so it provides the glue for them to do something without having to worry about digital devices crashing or being incompatible with the school system” (Ministry of Education, 2017)

The technological advancements of mobile devices and the Apple iOS and Google Android apps platforms over the past decade has enabled users the opportunity to learn Computer Science and Computer Programming for free or paid applications. Examples include Lightbot (SpriteBox LLC, 2022) on iOS and Grasshopper (Grasshopper, 2022) on Android. Google’s Grasshopper JavaScript app offers the opportunity of developing Computer Science skills on a mobile device backed by Google’s extensive learning resources (Google For Education, 2022; Grasshopper, 2022). There are hundreds of apps available to learn Computer Science and Programming (Google Play, 2022) including ScratchJr. “Overwhelmingly the experience of using mobile digital devices for learning is presented as a positive experience regardless of the application or type of mobile device used(Al-Zahrani & Laxman, 2016). “Mobile device use has become nearly universal worldwide, which can be seen from the increase in the number of mobile subscriptions per 100 people, from 12.075 in 2000 to 98.622 in 2015. Thus, it is not surprising that mobile devices are increasingly used for pedagogical purposes(Sophonhiranrak, 2021).

 

There are numerous Computational Thinking Computer Science and Computer Programming learning resources on the Internet which include; Khan Academy’s free Computer Science and Programming curriculum (Khan Academy, 2022) the thousands of professional and amateur YouTube Computational Thinking, Computer Science and Programming instructional videos (YouTube.com, 2022a, 2022b, 2022c), the Massachusetts Institute of Technology OpenCourseWare platform (MIT OpenCourseWare, 2022) and MOOC platforms like Coursera (Coursera Inc, 2022), Edx (edX LLC, 2022), Udacity (Udacity Inc, 2022), Future Learn (FutureLearn, 2022) and Sololearn which offers free and paid account learning opportunities in more than 20 Computer Science courses including Python, C, C++, C#, Java, JavaScript, R, Kotlin, PHP, Swift and Ruby supported by a social network of more than 48,000,000 community members (Sololearn, 2022).

International academic consensus is that Computational Thinking is described as an essential skill set for the 21st Century (Harris, 2018; Lamprou & Repenning, 2018; Tang et al., 2020). It makes strategic sense for teachers and students to take advantage of the convenience of their mobile devices and online or app based learning resources to learn Computational Thinking, Computer Science and Computer Programming in their own time on their own devices or as part of a hybrid learning construct or in school classrooms time “undergraduate programs increasingly involve students using mobile devices for classroom activities” (Sophonhiranrak, 2021)

5.3 Teachers Professional Development

The academic research for this dissertation has established that there is a global need for teaching and learning Computational Thinking, Computer Science and Computer Programming in education and that teachers are at the forefront of enabling students to experience learning outcomes that relate to these three skill sets. “Teachers have a key role in implementing a Computational Thinking curriculum, and if they find the language used in the curriculum to be challenging then this can be a barrier to achieving the intention of the curriculum(Munasinghe et al., 2021)

 

There are barriers for teachers new to computing and some academic research has found conflicting conclusions on teachers' understanding of these topics. “In some concepts presented in Computational Thinking as a foundation for Computer Science, teachers are already quite competent but in many cases primary teachers are ill prepared to teach the subject(Harris, 2018). “Teachers new to computing who are not familiar with technical jargon can feel like they have landed in a foreign world, making them reluctant to take on the subject, and potentially leading to misconceptions and misunderstandings in the classroom. The diversity of technical words, metaphors, and phrases in different contexts can make their meanings confusing, ambiguous or misunderstood for the diverse user groups in computing education(Munasinghe et al., 2021). “We observed issues and misconceptions that are a symptom of the large amount of new material and terminology that these topics introduce(Duncan et al., 2017). “There is a lack of teacher training for Computational Thinking, this indicates that fostering Computational Thinking is still a challenge due to only a few teachers being trained with the knowledge and skills to integrate Computational Thinking into course curricula(Tang et al., 2020).

Other considerations that compromise teachers professional development (PD) for learning Computational Thinking, Computer Science and Programming include;

  • Board of Trustees and senior management not prioritising PD for these subjects

  • Management and teachers not understanding the importance of these subjects

  • Complexity of integrating these subjects into existing school curriculum

  • Complexities of adding these subjects as new classes to existing timetables

  • No or minimal PD timetable allowance for teachers to learn these subjects

  • Teachers unwilling to spend their own time learning these subjects

  • No financial incentives for teachers to learn these subjects  

  • Understanding the complexities of technical jargon of these subjects 

  • No or only a few in school experts who can provide PD for these subjects

  • There are few external providers offering PD for these subjects

Research from some pilot initiatives in primary schools involving CS Unplugged Computational Thinking learning resources in Christchurch New Zealand have found conflicting results; ​​”Typical primary school teachers who are new to this subject material and have self-reported low levels of confidence(Duncan et al., 2017). “Some teachers in the pilot are embracing the new material and many have reported that through Computational Thinking activities they are also teaching other curriculum areas, and hence the impact on teaching time is relatively low. Some teachers have observed that students who were previously disengaged with their learning are drawn to the Computational Thinking exercises because they are using materials and movement to solve problems(Ministry of Education, 2017).

 

Contrary to these primary schools initiatives, there are currently no academic papers that relate to research that supports New Zealand secondary school teachers' professional development experiences or instances of integrating Computational Thinking into their senior curriculums.

 

International research suggests that; “New comprehensive approaches are needed to cope with the complexity of cognitive processes related to Computational Thinking. To help teachers assess Computational Thinking skills, new tools and criteria are required. Support from national or transnational research programmes could prove instrumental in achieving this goal. The introduction of Computational Thinking in the curriculum is creating a strong demand for large-scale in-service continual professional development (CPD), as many teachers did not learn about Computational Thinking in their initial education. It is of paramount importance that teachers and school staff should be provided with training opportunities that strongly focus on Computational Thinking pedagogy and hands-on learning which can be easily transferred to the classroom. In addition, policy actions could also include peer exchanges and community building to enable the sharing of best practices among teachers(Bocconi et al., 2016).