Computing in the curriculum: Challenges and strategies from a teacher’s perspective
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Abstract
Computing is being introduced into the curriculum in many countries. Teachers’ perspectives enable us to discover what challenges this presents, and also the strategies teachers claim to be using successfully in teaching the subject across primary and secondary education. The study described in this paper was carried out in the UK in 2014 where teachers were preparing for the mandatory inclusion of Computing into the curriculum. A survey was conducted of over 300 teachers who were currently teaching Computing to elicit their perspectives on challenges and strategies. From the analysis of the data, extrinsic and intrinsic challenges were identified for both teachers and students. In addition, a variety of pedagogical strategies were recommended by teachers from their own practice. In categorising approaches taken by teaching to support students five key themes emerged: unplugged type activities, contextualisation of tasks, collaborative learning, developing computational thinking, and scaffolding programming tasks. Further investigation could support whether these strategies can alleviate the challenges of teaching and learning of Computing for students and teachers. In particular developing student resilience in Computing is seen as a challenge while not many strategies are suggested. The results of this study will be useful for teachers who are new to the teaching of Computing.
Keywords
Computer science education Computing in school Inservice teacher education Computing curriculum1 Introduction
Computing^{1} is being introduced as a new subject in the school curriculum in many countries, and as an important part of informal learning opportunities in others. This brings with it both excitement and challenges, as for any new subject. For teachers facing curriculum change, how to teach it is very pertinent. Introducing new content does not merely mean that teachers have to equip themselves with new subject knowledge, which of course in many cases they do (Brown et al. 2013; Sentance et al. 2013; Thompson and Bell 2013). Teachers also need to learn appropriate pedagogies for delivering a new subject, particularly in those aspects of computer science that relate to algorithms, programming and the development of computational thinking skills.
Recent literature relating to computer science education in school highlights a number of ways of making computer science concepts accessible, engaging and fun, and more importantly, giving students a deep understanding of these concepts.

What pedagogical strategies do teachers report work well for teaching computer science in school?

What challenges do teachers report that they face?
Statements made by teachers who are currently teaching Computing in school have been coded, categorised and analysed, describing both successful strategies for teaching and the difficulties they face. The results reported in this paper are timely and relevant to teachers and teacher educators in the field of Computing, and we recommend that further investigation is carried out around the impact of the strategies suggested in primary and secondary education.
This paper also contributes to the area of pedagogical content knowledge (PCK) in Computing. PCK is the knowledge that a teacher has about how to teach their subject (Shulman 1986).
1.1 The ‘unplugged’ approach
Constructivist theory, based on the work of Dewey (1938); Piaget (1950) and Bruner (1996) suggests that learning is a cumulative and active process during which the student constructs knowledge and meaning for themselves as they learn, connecting with, and explaining new knowledge in terms of, what they already know. Constructivist learning theories applied to computer science emphasize the active, subjective and constructive character of knowledge, placing students at the centre of the learning process (BenAri 1998). Specifically, constructivist learning, based on students’ active participation in problemsolving and critical thinking, has profoundly influenced the teaching of programming (BenAri 1998).
Experiential learning that stems from constructivism describes the design of activities which engage students in a very direct way. Working with tangible real world objects is a central tenet of Papert’s constructionism (Papert and Harel 1991) (which builds on constructivism). Thus, constructivist principles support the strategies of using more kinaesthetic and active approaches to teaching in the computer science classroom. In Computing this is embodied in the ‘unplugged’ approach.
The “unplugged” style of teaching refers to the use of activities to teach computer science concepts without the use of computers. It originated with the CS Unplugged project in New Zealand (Bell et al. 2009; Nishida et al. 2009) and has resulted in many related, kinaesthetic activities which stimulate an understanding of a concept in a very concrete and practical way. In a similar way, CS4FN (Computer Science for Fun) (Curzon et al. 2009) have generated many unpluggedstyle engaging activities and approaches by emphasising the importance of analogy as well as a kinaesthetic activity.
1.2 Embedding computational thinking
A key consideration in computer science pedagogy needs to be the development of computational thinking skills. Computational thinking was only recently popularised as a concept in 2006 by Wing (2006) – the original definition stems from Papert (1996) – but teachers of computer science have been facilitating these skills in their students for as long as this subject has been taught. Wing claims that computational thinking is for everyone and involves “solving problems, designing systems and understanding human behaviour, by drawing on the concepts fundamental to computer science”. (Wing 2006, p. 34).
For teachers in England, guidelines have been developed recently suggesting how computational thinking can be explicitly taught as part of the new curriculum (Csizmadia et al. 2015). Computational thinking, according to these guidelines, is divided into a series of overlapping skills: abstraction, algorithmic thinking, generalisation and evaluation.
Many have recently suggested ways of implementing computational thinking into the curriculum (Barr and Stephenson 2011, Webb and Rosson 2013, Brennan and Resnick 2012, Lee et al. 2011, Selby 2012, Yadav et al. 2011, Van Dyne and Braun 2014, Sengupta et al. 2013). In our research we find teachers describe using a variety of activities that develop computational thinking skills in learners.
1.3 Learning to program

Code walkthroughs

Writing algorithms in groups

Insert comments in pairs into existing code

Develop code from algorithm in pairs

Find the bugs in code (Van Gorp and Grissom 2001).
Reading and tracing code is also important in supporting the learning of programming (Lopez et al. 2008) and being able to do this is a precursor to the problemsolving skills needed to write code (Lister et al. 2004). Tracing code refers to the process of stepping through a piece of code, often by hand, and noting the values of variables as the program proceeds. Lister later describes that novices need to be able to trace code with more than 50 % accuracy before they can begin to confidently write programs of their own (Lister 2011). In our study we were interested to see which pedagogical strategies were being used in the classroom by the teachers, and how teachers were supporting students in learning to read and write program code.
A final area of interest is the extent to which teachers provide a real world context for learning and relating it to students’ interests and understanding and the value of a rich discourse regarding concepts (Grover and Pea 2013).
1.4 The teachers’ perspective
Black et al. carried out a study in the UK where they asked Computing teachers how they felt they could make the subject interesting (Black et al. 2013). The key aspects that they identified were the importance to teachers of making Computing fun and relevant. In carrying out our research we were interested to see whether the teachers’ comments aligned with this study; in addition we asked more specifically for actual strategies that teachers use in their classroom that they feel to be effective.
In a similar way to Black et al., this paper focuses purely on the teacher’s perspective in addressing these questions. Diethelm et al. emphasise the importance of the teacher’s perspective to our understanding of computer science education as the teacher “may work on many different abstraction levels or apply very different teaching methods for the same topic of the curriculum” (Diethelm et al. 2012, p. 167). We wish to identify what these methods are, in particular identifying common themes that may help to provide guidance for teachers new to teaching the subject, as well as providing actual examples of teachers using effective strategies as we enter a phase of education when more and more students are studying Computing in school.
Section 2 gives details of the study. In Section 3 we then report on the results of the content analysis that was used to analyse the responses of the teachers. In Section 4 we draw out how this can contribute to the general area of pedagogical content knowledge in the subject, and then suggest strategies to overcome intrinsic challenges facing teachers.
2 The study
2.1 The context: Change in the curriculum
The UK has seen fastpaced change in the area of computer science education in the last few years (Brown et al. 2013; Brown, Sentance, Crick, & Humphreys, 2014). The state of computer science education is different in the four parts of the UK, with England having just implemented an ambitious new curriculum in Computing, to be taught from ages 5–16, and with a strong focus on computational thinking. This has been preceded by two years of preparation, as new qualifications were introduced and the draft curriculum proposed. Many schools and teachers in England had implemented elements of the Computing curriculum prior to the official starting date of the Computing Programme of Study in September 2014, as a void was left by the disapplication of the existing curriculum subject, Information and Communication Technology (ICT), in January 2012 (Brown et al. 2014).
In the UK there is a strong subject association for computer science teachers, Computing At School (Brown et al. 2013). Through this grassroots community of practice teachers are able to share resources, share experiences and attend local events. The participants of this study were to a very large extent members of this community. In the data collected in this study, they describe the experiences, successful strategies, and also the frustrations, of teachers who have begun to teach Computing in school over the last few years.
The Computing Programme of Study for the new English Curriculum (Department for Education 2013) is based on computational thinking principles, and thus teachers of computer science welcome guidance on how to deliver computational thinking skills, which is beginning to emerge.
2.2 The study: Methodology
A wideranging survey was carried out in February 2014, specifically targeting members of Computing At School (CAS), although invitations were extended widely. The survey was publicised via the CAS forum, as well as through social media channels. The survey included questions about teachers’ location and work situation and also the amount of Computing they taught, the confidence they had in their skills to do so and whether they were involved in examination classes. The survey also included many other questions about participation in professional development activities and engagement with Computing At School in general, which are not reported on in this paper.
 1.
What good techniques/strategies have you found for helping students to understand programming?
 2.
Please describe any good techniques/strategies you use for helping students to understand other aspects of Computing?
 3.
What difficulties, if any, have you experienced teaching programming?
 4.
What difficulties, if any, have you experienced teaching other aspects of Computing?
In the context of this survey, teachers in the England understand “other aspects of Computing” to be nonprogramming topics in the curriculum, which include learning about hardware, networking, data representation and logic (Department for Education 2013).
1417 members completed the wider survey (1126 of whom were practising teachers), with 339 teachers contributing at least one free text answer to the free text questions. In this paper we primarily focus on the 339 responses given by this selfselecting group of teachers but include reference to their other answers to survey questions where relevant.
The data were collected by an online questionnaire which was then input into qualitative data analysis software. The data consisted of the four free text questions described above, plus responses that these teachers gave to the other questions in the wider survey.
Coding scheme used (strategies)
Strategies – coding scheme used  

Algorithms (link to)  Games  Relate to real world activities 
Block to text strategies (use of)  Give feedback immediately  Robotics 
Break down/decomposition  Interactive lessons  Scaffolding 
Celebrate progress  Keep simple  Start children young 
Code manipulation  Learn theory through coding  Tangible interfaces 
Collaboration  Learn through examples  Team coding/pair programming 
Computational thinking  Learn through mistakes  Tutorials 
Contextualisation  Lots of practice/Little and often  Unplugged strategies 
Demonstration and modelling  Make it achievable (break down)  Use of videos 
Develop troubleshooting skills  Make it fun  Use of examples 
Differentiation  Mathematical skills  Use of handson experiences 
Discussion and questioning  Minimise syntax  Use of pseudocode 
Emphasise problem solving  Online learning  Use of simple IDEs 
Emphasise similarities  Peer mentoring  Use of variety of activities 
Flipped classrooms  Provision of support  Use of visual prompts 
Flowcharts  Reference to particular software  Work at own pace 
Coding scheme (Challenges)
Challenges – coding scheme used  

Teachers and assessment  Teachers’ lack of time  Students and documentation 
Teachers and coding focus  Teachers recruiting students  Students and expectations 
Teachers and differentiation  Teaching approaches  Students problemsolving 
Teachers and digital literacy  Teachers are underambitious  Students starting too late 
Teachers and dry topics  Students and resilience  Digital divide 
Teachers and funding  Students and instructions  Gender issues 
Teachers and lack of training  Students and literacy  Students not suitable 
Teachers and large classes  Students and Maths  Choosing resources 
Teachers and programming  Students and practice  Finding quality resources 
Teachers and results  Students and remembering  Lack of resources 
Teachers and subject knowledge  Students lack confidence  Physical Computing issues 
Teachers and troubleshooting  Students not engaged  Technical problems 
Teachers’ lack of support  Students not understanding 
Although two questions were asked about strategies and two questions about challenges, the answers received in some cases did not relate to the specific question. Because of the content of the data it was not possible to report on the particular strategies for programming and those on other aspects of the curriculum. All answers under strategies were thus analysed together.
2.3 The study: Participants
We are discussing here three groups of respondents – 1417 survey respondents as a whole, of whom 1126 were teachers. We then have a selfselecting sample of 339 teachers who completed the free text questions. From this sample we identified that 97 % (N = 329) were members of CAS, as opposed to only 88 % (N = 1256) of the 1417 people that completed the survey, including those who chose not to answer questions about their practice. This may be because members of CAS may be more likely to support a piece of research that is presented to them by CAS itself, or may be that they are a more confident community by virtue of their engagement with CAS, but we cannot know this.
Distribution of respondents across UK
UK  Whole survey population  Selfselecting sample  

England  1028  91.3 %  314  92.6 % 
Northern Ireland  7  0.6 %  3  0.9 % 
Scotland  47  4.2 %  12  3.5 % 
Wales  16  1.4 %  3  0.9 % 
Outside UK  28  2.5 %  7  2.1 % 
Total  1126  339 
Type of school and number of teachers
Type of School  Age group  Whole survey population  Selfselecting sample  

Primary  4–11  229  20 %  55  16 % 
Middle  8–13  16  1 %  5  1 % 
Secondary  11–16 or 11–18  841  75 %  260  77 % 
Sixth Form College  16–18  24  2 %  12  4 % 
Further Education  16–19  16  1 %  7  2 % 
1126  339 
Number of teachers for different key stages (agegroups)
Key Stages  KS1  KS2  KS3  KS4  KS5 

Ages  5–7  7–11  11–14  14–16  16–18 
Teachers from whole survey  152  257  809  798  560 
Teachers from selfselected sample  43  74  258  253  194 
Here it can be seen that our selfselecting sample differs from the overall respondent population of teachers as they are teaching more hours per week overall, with 69 % teaching at least 5 h a week of Computing. This sample includes primary teachers who teach many other subjects as well and would not be likely to teach more than one or two hours of Computing every week.
3 Findings
The findings of the study will be divided into Challenges and Strategies. In the study we asked questions about strategies before the “challenges” questions, but present challenges first here as it is then possible to see that teachers are suggesting strategies that can overcome the challenges faced by themselves or others.
Both researchers coded the data as described above and the interrater reliability for the researchers was found to be Kappa =0.601 for coding of strategies and 0.684 for coding of challenges. 0.41–0.60 is moderate agreement; 0.61–0.80 is substantial agreement (Viera and Garrett 2005) so these figures can be seen to be on the moderate/substantial agreement boundary. During the analysis of the challenges one of the codes “teaching and coding focus” was removed due to a lack of common understanding of the code.
3.1 Challenges
In this section we report on the challenges that teachers report on with respect to the teaching of Computing. A number of themes emerged from the analysis of the data.
Overall it can be seen that all of the challenges coded fell into the categories that we had broadly identified as teacher, student and resourcerelated. Of 855 codings, 40 % (N = 342) related to challenges directly experienced by the teacher, 38 % (N = 325) related to challenges which could be seen to difficulties experienced by the student, and 16 % (N = 138) related to resources. In 50 cases, just 6 %, teachers reported to have no problems with respect to teaching Computing.

Teachers’ own subject knowledge

Students lack of understanding of content

Technical problems in school

Differentiation to meet different levels of ability

Students willingness or ability to problem solve
Challenges: most commonly occurring themes
Challenges  Teacher challenges  Number of cases with mentions 

Challenges relating to teachers  Subject knowledge  97 
Differentiation  59  
Lack of time  53  
Approaches to teaching  52  
Dry (difficult to teach) topics  33  
Assessment  25  
Lack of support  20  
Challenges relating to students  Students not understanding  76 
Students and problem solving  59  
Students’ resilience  46  
Students not engaged  40  
Students ability in Maths  26  
Students literacy skills  14  
Students not remembering  13  
Students not practising  13  
Challenges relating to resources  Technical problems  61 
Lack of resources  43  
Finding good quality resources  22 
Typical quotes from teachers illustrate these points.
3.1.1 Challenges for teachers
“...the sheer time involved in learning the language, skills. I do self CPD daily, and have given easily 100+ hrs of my own time to building my own skill set up... “
“At the moment it is my own underpinning knowledge about the construction of solutions to problems. I have worked through several training booklets and courses but it is just the ability to solve problems that the students would come across in the system that they are using.”
“The different abilities of students especially when they come in from primary… some are wellversed in graphical programming environments.”
“The gap between those that engage and achieve very quickly grows at an alarming rate. When introducing block coding in Scratch to my class, all were unfamiliar with anything like this, I had some pupils baffled and many selfexploring. I have found the ability gap to be much bigger than any other subject or topic and it seems to be down to the way in which the children think.”
“Pupils understand at different pace so trying to keep the high flyers occupied and engaged without losing the less able pupils...”
“…finding ways to encourage pupils to logically think through their problems, rather than ask for assistance at the first sign of difficulty.”
“I have very little experience of teaching that will prepare pupils for an exam... nearly everything I have ever taught has been coursework based, so I am not confident my lessons will arrive in pupils’ memories!”
“There is little guidance on assessment and I fear that many schools will just head down a ‘death by scratch’ approach with some children simply following instructions”
“…some of the theory is quite dry so finding ways to make it interesting to students is a challenge.”
3.1.2 Challenges related to students
“In addition, many students want to jump before they can crawl and want to be developing complex programs without any understanding of the steps en route“
“Linking the theoretical concepts to the practical application of those concepts; students tend to try to learn ‘rules’ and then cannot apply the theory to their practical work.”
“Getting across the concept of a variable and why / how variables are used is always a challenge  simple metaphors help, but this is perhaps the biggest hurdle pupils have. Bridging the gap from graphical programming (Scratch etc.) to textbased programming is a challenge …”
“Pupils find it very difficult to think computationally. Breaking a large problem in to smaller ‘chunks’ is not something which comes easily to them.”
We also find students’ problem solving skills are underdeveloped. So we could as a student to code a FOR loop to iterative for 1000 times. Or to create an IF statement, etc. They are fine with everything individually. However, ask them to create an algorithm to solve a problem, which involves everything they have learnt, it can be a problem.
“Literacy is a big issue when teaching Computing; this has been the main stumbling block when trying to introduce variables, functions etc. “
“Keeping pupil interest going and maintaining their attention; weaker pupils coping with mathematical concepts, such as binary; tying the different elements together to ensure pupils understand how they mesh, e.g. relevance of binary code, logic gates.”
“We need to let students know there is more to Computing than [company name] and controlled networking environments, they need to learn to be responsible for their actions on the computers and understand how their actions can be traced  because one day that might be the job they are doing. I feel this will get more girls interested and keep more boys focused and give students a much more realistic view of what Computing is all about. It is a very practical, hands on subject and we need to be reflecting this in our teaching style.”
“Students giving up easily. Not wanting to check their code. Finding it too difficult and not being prepared to “find out for themselves”. Students are too spoon fed in ICT, and other subjects, and appear not to have the thinking skills required for this subject. I have even had quite a few students leave my CS course because they found it hard, and gave up!”
“Maths abilities of students also appears to have a big influence on their understanding of logic and sequencing.”
The analysis of teachers’ qualitative responses highlights the challenges of students reading, analysing and synthesising problems in order to abstract the essential data to solve a problem. In addition, a number of teachers expressed their concern about students not being able to read a section of code and detect grammatical, logical and syntactic errors that exist within that code. Teachers identified the need to encourage students to develop, embrace and articulate a common Computing vocabulary so that students are aware of technical keywords and use them correctly.
Teachers expressed the challenges of identifying successful strategies to engage students in the Computing classroom, emphasising an understanding of the ubiquitous nature of Computing and the issue of disaffected and disengaged female students who do not see the relevance of the subject to them.
“Pupils struggle to remember what has gone before without lots of practice”
“Students do not realise nature of subject before they start and sometimes find it very challenging”
3.1.3 Challenges relating to resources
The analysis of teachers’ qualitative responses highlights a variety of resourcerelated challenges which include possessing adequate hardware and software resources to teach the subject, sufficient funding to purchase resources for a new subject, and software resources correctly installed, configured and maintained to run correctly on the platform that the school operates. For example, a teacher commented that there is a “Lack of resources but CAS is helping to change that”.
Teachers expressed their frustration of a perceived lack of support and understanding from their managers of the complexities of teaching Computing and unwillingness on the part of technical staff to contemplate installing software that they consider could compromise the integrity and security of the school’s computer network.
A number of teachers conveyed their concerns regarding technical staff reluctance to maintain and troubleshoot installed software on either the computer network or standalone computers, for example describing “technical difficulties with getting software to work on the school network”.
Overall, there were some differences between secondary and primary teachers in their responses about difficulties. More primary teachers (40 %) mentioned lack of subject knowledge in computer science being a difficulty than secondary (26 %). More secondary teachers (17 %) mentioned differentiation being problematic compared to primary (7 %). More secondary teachers (10 %) said their students lacked resilience than primary (5 %).
3.2 Successful strategies used by teachers
Strategies: most commonly coded themes
Strategy  Number of cases coded at this node  Strategy  Number of cases coded at this node 

Unplugged strategies  70  Peer mentoring  32 
Reference to particular software  55  Use of examples  32 
Relate to real world activities  49  Algorithms (link to)  29 
Use variety of activities  49  Demonstration and modelling  27 
Lots of practice/Little and often  47  Learn through examples  27 
Use handson experiences  45  Contextualisation  25 
Break down/decomposition  40  Use of videos  25 
Code manipulation  38  Team coding/pair programming  24 
Scaffolding  38  Develop troubleshooting skills  23 
Emphasise problem solving  32  Collaboration  22 
Table 7 shows that teachers emphasised unplugged, handson, contextualised activities and the importance of lots of practice. Approximately the same number of teachers mentioned working on tasks away from the computer as mentioned a particular software package that they used. The study looks entirely at free text comments with suggestion within the question; there are themes emerging quite clearly from this data around using activities away from the computer that promote understanding. These will be discussed in more depth in the next section.

Learning away from the computer (unpluggedstyle)

Collaborative working

Computational thinking

Contextualisation of learning

Scaffolding programming tasks
Coded themes linked to key strategies
General theme  Coded theme  Number of cases 

Unplugged/practical activities  Unplugged strategies  70 
Handson experiences  45  
Collaborative work  Team coding/pair programming  24 
Peer mentoring  32  
Collaboration  22  
Computational thinking  Break down/decomposition  40 
Problem solving  32  
Algorithms  29  
Scaffolding programming tasks  Scaffolding  38 
Code manipulation  38  
Contextualisation  Relate to real world activities  49 
Using examples  32  
Learn through examples  27  
Contextualisation  25 
Each of these areas of focus will be exemplified in turn.
3.2.1 Unpluggedstyle or kinaesthetic activities
“For example I use clear plastic drinking cups as memory locations and label them as variables or when demonstrating an algorithm like bubble sort add data (on pieces of paper).”
Many of these activities are designed to promote both collaboration and computational thinking skills. In fact, whether the activity takes place on the computer or not may not be what is interesting. The key link between the statements made by teachers seemed to be their impression that actually physically being engaged in the activity was conducive to the students’ learning. This is an area which would benefit from further research.
3.2.2 Collaborative working
“…Developing digital leaders in students who can support others…”
“Decomposing sample problems together as a class then teamcoding …they can use peers for discussion of specific problems. …”
3.2.3 Computational thinking
Analysis of teachers’ qualitative responses indicates a number of computational thinking concepts and processes that teachers want to promote and develop their students’ competence in through using a variety of teaching and learning activities. These concepts and processes include: logic (algorithmic) thinking, decomposition, problem solving and abstraction (Brennan and Resnick 2012).
“Breaking down the problem then breaking it down again then breaking it down again... …”
“Organise the learning so that the pupils develop their programming skills using decomposition and abstraction. ….”
3.2.4 Contextualisation of learning
“Scale it back to basics and use reallife examples for the activities e.g. making tea. Use lots of visual aids to help pupils and online resources to help scaffold activities.”
3.2.5 Scaffolding programming tasks
“… giving code on paper not electronically, so they have to type it in, think about what they are typing and fix the errors that occur when trying to compile the program …”
“Discussion of what a specific algorithm does, then running trace tables on small programs …”
Other strategies described included “scaffolding” as the student is given part of a program to extend, and programs to debug. Typing in code to give more chance that the program would work, but involving debugging errors caused by transcription errors is another supportive strategy for early programmers reported by teachers.
4 Discussion
Teachers reported a range of different challenges that they faced when teaching Computing. Some of the challenges mentioned relate to the teachers’ own difficulties – for example, not being confident in the subject matter or not being able to differentiate sufficiently for a mixedability group, and other comments focus on the fact that the students have difficulty understanding the material and in problem solving.
4.1 Intrinsic and extrinsic challenges
A framework for viewing challenges reported by teachers
Challenges  

Intrinsic  Extrinsic  
Teachers  Subject knowledge Differentiation (skills in) Approaches to teaching topics (pedagogy)  Assessment Resources Lack of support Lack of time Technical problems 
Students  Mathematical aptitude Literacy skills Resilience Problemsolving skills Not understanding Engagement  Time to practise School and others’ expectations 
Teachers may be working to improve on the challenges that they face that are intrinsic to them, for example their own subject knowledge and teaching approaches, but be frustrated by the challenges over which they have less control, such as time in the curriculum or technical support. Teachers report on challenges that we have defined as intrinsic to the students; in the way that these are presented, they appear to be described as extrinsic to the teacher. The teachers report the students’ lack of understanding of the subject or lack of engagement as a problem to them. However the development of strategies by the teacher to overcome the difficulties experienced by the student may be within their reach as their experience of teaching Computing increases.
The question remains as to what schools can do to address these challenges. Clearly teachers need more training (Sentance et al. 2013) and to develop confidence in their pedagogical skills with relation to Computing. However there is much that could be done by schools to alleviate the challenges facing teachers in the context of curriculum change. Teachers need more support from their headteachers and leadership teams to implement new courses and develop resources. They need access to robust technical solutions through their school’s technical support departments. Students need time to practice the new skills without initially facing unrealistic expectations while the new subject is bedding in. All these things are possible, although there may be financial restrictions on schools’ ability to implement them.
However building students’ resilience and ability to learn from mistakes may take more time. Developing problemsolving and other computational thinking skills is challenging when the subject is mandatory for all students in the school rather than a small selfselecting group as an extracurricular option. Building learners’ confidence is key and understanding and then celebrating small successes will be important.
Suggested strategies to address these challenges will be discussed in the next section.
4.2 Strategies adopted by teachers
 1.
Unplugged type activities
 2.
Contextualising activities
 3.
Collaborative learning
 4.
Developing computational thinking
 5.
Scaffolding programming tasks.
BenAri (1998) advised teachers: “Do not run to the computer”, and it seems that teachers are taking this advice in using a variety of other strategies to get concepts across. In addition, the use of collaborative work, peer mentoring, pair programming and other strategies is helping teachers to establish computational thinking skills in young students. What is clear is that there is a change for teachers.
4.2.1 Change in teaching strategy
One of the main outcomes of this study is that the ways in which computer science elements of Computing are taught are different to methods previously used in delivering ICT. Teachers have provided a range of approaches that they use that are different to those that they previously used delivering ICT in the curriculum. They also describe that students also have to adapt to new ways of teaching and different types of content, particularly older students who had been used to the same teachers delivering a different style of lesson.
[It is] “ a whole new style of teaching as for the past 10 years I have been demonstrating skills in... software, and getting pupils to show evidence they have learnt those skills. With Computing I actually have to teach, and get difficult concepts across, and need to get out of the habit of simply showing pupils how to do something and then asking them to do the same thing. I am finding it hard not to just show how to solve a programming problem, and instead teach pupils to think for themselves.”
“Often the subject is viewed as ICT and most students do not know the difference. For many it comes as a shock that there is a lot of problem solving as opposed to ICT”

Active learning experiences which involve the student (for example, unplugged, kinesthetic activities)

Learning by exploration (openended tasks, exploring programming environments)

Learning by solving problems (selfdirected projects, problemsolving)

Using examples that are relevant to students’ own experiences (relating to realworld experiences)

Openended discussion and working in groups (group tasks, team problemsolving).
“I’ve observed people teaching other subjects e.g. Maths and History and found that they have great strategies for managing learning content!”
4.2.2 Developing computational thinking
There are some aspects of computer science which may require specific approaches to teaching that do not necessarily transfer as well from other teaching experiences. Primarily this relates to supporting students with their computational thinking skills. Some guidance on computational thinking developed for the English curriculum (Csizmadia et al. 2015) suggests a range of strategies including “breaking down into component parts (decomposition), reducing the unnecessary complexity (abstraction), identifying the processes (algorithms) and seeking commonalities or patterns (generalisation)” (p. 9).

Manipulating/comprehending/tracing code (teaches evaluation and generalization)

Breaking down code/concept (teaches decomposition)

Developing algorithms (teaches algorithmic thinking, abstraction and evaluation).
4.2.3 The need to develop resilience
“If there is a problem, they want the teacher to correct it for them... they do not have to get it correct first time, but they do need the skills to be able to correct it and see why there was a mistake in the first place.”
This is one area of difficulty that was not readily addressed in strategies suggested by teachers. Being able to “deal with adversity”, “keep trying” or “learn from our mistakes” is obviously a life skill for all of us. However, this is particularly important when learning computer programming (perhaps less so in other areas of computer science theory). As all programmers know, learning to troubleshoot errors, and learning from errors, is the prime way of making progress in the acquisition of programming skills. This is a mindset that is alien to a lot of children in school, who are taught to seek success, not failure.
“I encourage pupils to have a go, make mistakes and then try to work out for themselves what to do when things don’t work the way they want”
“Students tend to understand the process better if they work through wrong answers, rather than being given program code each time”
“Letting them have a go and allowing them to get it wrong. They need to become problem solvers, not just the teacher telling them what to write. The students must code for themselves without too much intervention from the teacher in terms of theory. There has to be some of course, but after they have tried to figure it out first
Given that lack of resilience is a commonly mentioned challenge, it could be recommended that teachers focus more on strategies that build resilience in learners when they teach programming.
4.3 Limitations of the study
The intention in the study was to identify particular strategies for teaching programming and those for teaching other aspects of Computing, including theory, and similarly with challenges. However we were not able to do this, due to the nature of the data, as reported in Section 2.2. Some teachers described how they taught programming under the nonprogramming question and vice versa. This is a limitation because it means we have not been able to reliably compare strategies for different areas of the curriculum. Thus the proportion of answers relating to scaffolding programming tasks, which did not generally occur as answers to the nonprogramming question, may have been even higher had we been able to look at programming strategies alone. This could have possibly been avoided by more explicit signposting in the survey.
The teaching approaches described by teachers in this study are not claimed to be representative of all teachers teaching the Computing curriculum in England. The survey was promoted primarily through the Computing At School (CAS) website which has a large number of teacher members who teach Computing, in addition to a direct email to Computing At School members and use of social media. The four questions reported on in this paper were optional and teachers were asked if they wished to take part in a particular part of the research before being shown these questions. This means that the group of teachers answering are not only selfselecting, but they are also a group of teachers that are enthusiastic about teaching Computing and we have already reported that they demonstrate selfefficacy. Thus this study does not in any way attempt to claim that these strategies and challenges relate generally to all teachers of Computing.
The teachers participating in the survey are, in the majority, members of CAS, and as such have access to a lively and supportive grassroots community of teachers with whom they can exchange ideas and classroom resources. The presence and nature of this community of practice may well have an impact on the commonality between the approaches teachers are successfully using, as resources are freely shared and adapted and strategies for teaching discussed in facetoface sessions such as hub meetings. The possible limitation of this is the emphasis on unplugged activities in particular may be influenced by the amount of resources, posts and magazine articles on this topic that CAS members have access to. The community suggests good practice and teachers act on their suggestions. However, the fact that teachers mention use of these strategies implies that they have found them useful in the classroom in supporting learning.
We are not able to provide evidence for which of these suggested approaches is more effective in helping students to learn without more empirical research; thus another useful angle following on from this study would be to examine students’ own perspectives on how Computing is taught. This is recommended as an area of further investigation.
As another area of further investigation, we suggest that more research is carried out on the implementation of these strategies for learning Computing and the impact on students’ learning. The five themes identified here offer a clearly defined set of approaches to examine further.
5 Conclusion
This study has reported on a survey of Computing teachers in 2014 where a large selfselected sample (N = 339) answered free text questions about successful teaching approaches that they used for teaching Computing and challenges that they faced. The participants were selfselecting and mostly reported themselves as being confident in their delivery of Computing  thus the data gives us reports of good practice.
We have been able to identify a number of themes emerging from this data and also pinpoint where challenges may be intrinsic or extrinsic to the teacher. We hope that the strategies suggested here may help those teachers who are still moving into Computing teaching themselves. The discussion in this paper can contribute to work in teacher education to support teachers who are beginning to teach Computing – as more countries move to introduce the subject in the curriculum.
Overall, given that we would like this study to be able to offer guidance to teachers on how develop their Computing teaching skills, we can suggest that one specific focus should be on supporting students to develop resilience and the ability to learn from mistakes. Together with other strategies suggested by the teachers whose comments are reported here, this may lead to an easier acquisition of programming skills, and subsequently computational thinking skills.
Footnotes
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