{"id":516,"date":"2019-01-17T12:00:00","date_gmt":"2019-01-17T12:00:00","guid":{"rendered":"http:\/\/www.jameshatton.co.uk\/blog\/?p=516"},"modified":"2024-02-26T10:57:21","modified_gmt":"2024-02-26T10:57:21","slug":"what-makes-an-effective-computing-lesson","status":"publish","type":"post","link":"https:\/\/www.jameshatton.co.uk\/blog\/2019\/01\/17\/what-makes-an-effective-computing-lesson\/","title":{"rendered":"What Makes an Effective Computing Lesson"},"content":{"rendered":"\n

Introduction and Context<\/h2>\n\n\n\n

The adoption of computer science (CS) within the national curriculum (NC) was only four years ago in 2014 and arguably UK secondary school education was slow to embrace the new CS curriculum \u2013 Busby, H (2016). A change in paradigm between the skill-focused delivery of ICT and the conceptual-focus delivery of CS is required. The Department of Education ([DfE], 2013) clarifies the end-goal of CS in the first sentence of the NC for Computing: \u201cA high-quality computing education equips pupils to use computational thinking and creativity to understand and change the world.\u201d<\/p>\n\n\n\n

The vast array of education literature, from policy to professional guidance and academic research, is indicative of many factors that can influence the effectiveness of a CS lesson. A traditional approach to understanding the effectiveness of a lesson would be judgement of tangible pupil output against learning outcomes. In a computer science lesson this may appear to be code but there are inherent pitfalls because it is possible for a pupil to simply copy and execute code without conceptually understanding what a program is doing. <\/p>\n\n\n\n

A useful endpoint, then, to evaluate the effectiveness of a CS lesson would be to what extent a lesson helped students develop computational thinking (CT) skills; whereby programming serves as the formative assessment to ascertain the extent to which this understanding has occurred. The challenge to delivering an effective CS lesson is then essentially the challenge to teach children CT \u2013 appropriate to their stage of development. This assignment will explore the role of starter activities, within wider learning theories, in order to nurture CT skills.<\/p>\n\n\n\n

Review of Existing Literature<\/h2>\n\n\n\n

The fundamental aim of computer science is about utilising technology to solve problems. It is useful to retain a relatively vague definition because technology constantly evolves; and the subject encompasses everything from low-level programming of micro-controllers through developing neural networks. The element of solving problems need not be more specific because the problems could be real-world, which are simulated in software, or they could be purely conceptual (mathematical) \u2013 indeed computer science itself can generate its own problems to solve. An effective computer science lesson then delivers a skillset, a framework, to the leaner by which problems can be solved as the endpoint \u2013 as opposed to imparting knowledge itself (e.g. syntax).<\/p>\n\n\n\n

This skillset is CT: A phrase in usage since the 1980s but gaining prominence, and precipitating much debate, when Jeanette Wing (2006) wrote an article in a widely deployed and respected journal, stating that \u201cComputational thinking is a fundamental skill for everyone, not just for computer scientists.\u201d This indicates that CT provides deeper benefits to pupils than a narrow set of skills for a limited scope. CT is then the fundamental scientific framework with which problems are understood and practical skills can be employed. Table 1 summarises the aspects of CT. <\/p>\n\n\n\n

Table 1 Summary of CT aspects based on Sentance, S., Barendsen, E., & Schulte, C. (2018, Chapter 3.4)<\/em><\/p>\n\n\n\n

Aspect<\/td>Explanation<\/td><\/tr>
Logical Thinking<\/td> The ability to analyse problems and reach a solution. In CS, this is Boolean logic and constructing expressions based on operators (e.g. AND, OR, NOT). <\/td><\/tr>
Algorithmic Thinking<\/td> The procedures involved in solving a problem, which typically involves sequence, selection and repetition. <\/td><\/tr>
Pattern Recognition<\/td> Being able to recognise patterns provides the basis for generalisation or iterative\/recursive models; or being able to re-use solutions for various parts of solving a problem. <\/td><\/tr>
Abstraction<\/td> Regarded as the most important aspect of CT whereby detail is reduced to enable simplification and focus on the input and output. This is key to producing algorithms and models, which simulate real world complexity. <\/td><\/tr>
Evaluation<\/td> The ability to analyse whether a solution is correct and appropriate. In CS, this is usually against criteria of efficiency or resource usage, for example. <\/td><\/tr>
Automation<\/td>Understanding which abstractions and data representations are most appropriate for a machine to automate a solution. Distinguishing between which elements are best solvable by machine versus a human.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Sentance, S., Barendsen, E., & Schulte, C. (2018, p.30) states \u201cthere is little debate that computational thinking is about more than codifying a solution for execution by a computer through programming and that it is the loftier, more worthy goal of CT that we must strive to achieve through appropriate pedagogies even when students are engaging in programming\u201d. The next section will explorer wider theories on how this goal can be achieved.<\/p>\n\n\n\n

Learning Theories<\/h3>\n\n\n\n

Guidance can be found amongst the plethora of literature that has emerged over the last century to present various theories of how children learn and subsequently, how then best to teach. The earliest theories of learning are regarded as behaviourist approaches \u2013 what is observed and the idea of rewarding desired behaviours \u2013 operand conditioning. There are limitations to this approach and Pritchard, A. (2018, p.29) states, \u201cUsing a behaviourist approach in the classroom seems to be most effective when applied in cases where a particular child has a history of academic failure; where there is very low motivation and high anxiety; and in cases where no other approach has worked.\u201d<\/p>\n\n\n\n

The opposing, constructivist, view of learning is described by Pritchard, A (2018, p.37) as \u201cthe result of mental construction. That is, learning takes place when new information is built into and added onto an individual\u2019s current structure of knowledge, understanding and skills. We learn best when we actively construct our own understanding.\u201d The author continues to define four areas for learning as knowledge, concepts, skills and attitudes. Bates, B. (2015 pp. 46-48) summarises Vygotsky, a chief proponent of the constructivist perspective: \u201cknowledge and thought are constructed through social interaction with family, friends, teachers and peers\u201d and \u201clearning occurs through social interaction as being in the Zone of Proximal Development (ZPD)\u201d. Being in the ZPD is where learners \u201cdeveloped an understanding of a subject beyond their previous level of comprehension\u201d.<\/p>\n\n\n\n

Perhaps then a fundamental challenge to delivering an effective CS lesson, with the aim of nurturing CT, is to move away from the historically traditional approach of simply teaching programming on a computer. The layouts of many CS classrooms do not support this paradigm: There is a personal computer provided per child where children sit facing away from the collective, and this configuration does not readily lend itself to collaborative social learning. Pupils present with many barriers to learning and the preconception that CS is a solitary pursuit may be counter-productive, according to Zygotsky\u2019s model, where pupils desire social interaction to learn.<\/p>\n\n\n\n

Sentance, S., Barendsen, E., & Schulte, C. (2018, p.30) states: \u201cA couple of other elements, though not considered part of CT in earlier definitions of CT, are often described as common practices in computational problem solving. These include collaboration and creativity. Both are acknowledged as critical competencies for a new century, but they do have a special meaning in the world of computer science.\u201d<\/p>\n\n\n\n

Zygotsky, cited in Bates, B. (2015 pp. 46-48), developed the concept of scaffolding, which describes a teacher\u2019s role to support pupil development and outlined some principles:<\/p>\n\n\n\n

  • Build interest in the subject and engage with people.<\/li>
  • Break the given task into smaller sub-tasks<\/li>
  • Keep the individual or group focused on completing the sub-tasks but don\u2019t allow them to lose sight of the main task<\/li>
  • Use MKOs to support people<\/li>
  • Model possible ways of completing the task, which individuals can imitate and then eventually internalise (Bates, B., 2015 p. 47)<\/li><\/ul>\n\n\n\n

    In summary, scaffolding is the process by which a teacher models how to solve a problem and then steps back, in a more facilitative role, to only offer support where required as learners utilise their new-found knowledge and skills to further their learning.<\/p>\n\n\n\n

    This constructivist perspective to learning aligns appropriately with the evidence that \u201cMany computing concepts have links to everyday objects and real world ideas so the use of analogy is a powerful to scaffold students\u2019 understanding\u201d. (Sentance, S., Barendsen, E., & Schulte, C., 2018, p.92). Perhaps then a fundamental challenge to effectively teaching CT is to move away from the historically traditional approach of simply teaching programming on a computer, to using activities with which students are familiar. As this culture of collaboration is paramount to developing CT in order to deliver an effective CS lesson; the question then arises as to how this can be achieved and at what stage of the lesson.<\/p>\n\n\n\n

    Starter Activities<\/h3>\n\n\n\n

    Starter activities seem to be a de-facto component of lessons in secondary education and their benefits are widely acknowledge. Capel, S., Leask, M., & Younie, S. (2016, p.92) state \u201cIt is usual to begin with a starter task to engage learners from the very moment they enter the classroom.\u201d One of the benefits is to \u2018set the tone\u2019 of the following lesson \u2013 the classroom climate.<\/p>\n\n\n\n

    Classroom climate, as the embodiment of the routines, instructions, management of behaviour and interactions has long been viewed as critical to determining effective learning and teaching. Over two decades ago, through analysis of research, Wang, M., Haertel, G., & Walberg, H. (1993) placed the impact of classroom climate almost as high as, and second only to, student aptitude \u2013 illustrated by figure 1.<\/p>\n\n\n\n

    \"\"
    Figure 1 Table showing the average influences on learning – from Wamg, M., Haertel, G., & Walberg, H. (1993, p.79)<\/figcaption><\/figure>\n\n\n\n

    Simmons, C and Hawkins, C (2015, p. 68) state \u201cA good starter provides an opportunity to set the scene, excite children, provide essential information and pose big questions.\u201d \u2013 and that they are often used in order to set targets, demonstrate a skill or get pupils thinking. Lau, W. (2018, p. 83) refers to \u2018classroom culture\u2019 and informs a teacher: \u201cOnce you have established a positive learning culture in the classroom and your students are highly motivated and trusting, it will be possible to teach practically any computing topic.\u201d<\/p>\n\n\n\n

    Daniel Mujis and David Reynolds are well-respected experts in the field of educational practice, occupying senior posts at the University of Southampton as the Chair of Education and the Professor of Education Effectiveness, respectively. Their publication, in its fourth edition over nearly two decades, provides a strong insight into a range of considerations that discuss effective teaching, drawing on evidence-based research and states \u201cThe most important aspect of classroom climate is the relationship between teacher and pupils.\u201d \u2013 Muijs, D., & Reynolds, D. (2018, p.130 )<\/p>\n\n\n\n

    Student aptitude cannot be directly and immediately determined by the teacher, but classroom climate can be established by the teacher in constructing supportive teacher-student relationships. Dr Williams, an experienced teacher and academic, states that \u201cResearch tells us that the start of a lesson is the best time to engage the learner\u201d (Williams, S., 2016). Ergo, it seems that the start of the lesson is the most important time by which the teacher sets expectations of students and indicates what relationship will exist \u2013 the \u2018tone\u2019 of the lesson. Lessons in secondary school teaching commonly follow the formula of starter activity, main teaching and a plenary \u2013 albeit variation as appropriate does exist. The starter activity, then, seems perhaps the most relevant point at which to reinforce a supportive the student-teacher relationship. A core component of using Vygotsky\u2019s scaffolding model, as discussed earlier, is to \u201cBuild interest in the subject and engage with people.\u201d<\/p>\n\n\n\n

    The Department for Education and Skills (2004) publication was prior to the adoption of CS within the NC but nevertheless provides strong research-based insights into the usefulness of starter activities, along with guidance. It highlights the following outcomes that a successful interactive starter can achieve:<\/p>\n\n\n\n