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EduTech Africa 2019 – Coda

Last week I attended the EduTech Africa 2019 Conference in Johannesburg and would like to wrap up my thoughts on the conference with a few observations. Now that the dust has settled the thing that sticks out most in my mind is the clear recognition of the rise of Computer Science as a K-12 academic discipline. The government’s commitment to rolling out IT as a subject, and the focus on coding across all age groups has established a clear sense that Computational Thinking and Computer Science belongs in the core curriculum in all schools. The big question is then how we get there. The announcement recently that PISA Assessments, which offers international benchmarks in Maths & Science, will now include Computational Thinking and Computer Science is confirmation of this. Most of the talks I attended addressed the issue of how best to teach Computer Science in some form or other. Passionate teachers shared their best practice, and their failures. So, the coda to my reflections on the conference is really to address that question. Is there a best method to teach Computer Science?

NS Prabhu (1990) in answering the question of whether there is a best method of teaching or not, concluded that the key factor in teaching success lay with the teacher’s sense of plausibility, the teacher’s sense of self belief that what they are doing makes sense, how passionate they are. There is clearly a great deal of plausibility around the teaching of Computer Science at the moment. Obstacles are being dealt with as opportunities, and there is a very real sense that inventiveness and creativity can overcome the constraints of budget and lack of training.

The clear consensus amongst teachers seems to be that physical computing forms the best approach. Most presentations highlighted the use of coding in conjunction with 3D printing and robotics. My very first exposure to teaching computing was with Seymour Papert’s (1980) logo system. I did not have the turtles, using only the computer interface, but I tried to make it more concrete by using physical cards with shapes students had to emulate. Computer Science is a very abstract subject and needs to be concretised for students as much as possible. The cost of all the kit needed to do this is prohibitive.

I recently came across micro:bits which uses a web-based platform for coding. The code created is then downloaded as compiled hex code to the microbit chip which executes the code. But crucially it also has a web visualisation tool, which executes the code in the code editing window. The micro:bit controllers are themselves fairly cheap, but having a visualization tool means that more students can code at any one time. A class would need fewer physical chips at any one time. I have not yet been able to test the real thing, but it seems to me a perfect fit for the kinds of physical computing tasks I would wish to introduce. It uses a block coding interface, but you can toggle to program in JavaScript or Python, making it ideal for transitioning between block-based coding to the text-based fare students will need higher up the school. You can also design 3D printed parts for interesting projects.

But I digress, back to best methods. Another strong thread in the conference was computing for problem solving. I have to say that I am a little dubious about the whole Computational Thinking leads to better problem solving generally. I believe it leads to better problem solving in computational contexts, but transfer of skills from one context to another is always problematic in my view. Nevertheless, I do believe that students should be given real world problems to solve as far as possible and Computer Science teachers are leading the way in envisioning how coding could form a central plank in cross-disciplinary problem solving exercises. There was a great deal of talk at the conference about the need for teachers to “come out of their silos.” There is certainly no need for CS teachers to set projects divorced from the real world, or set problems narrowly about computers.

The final method that was raised at the conference was unplugged computing, an approach which involves modelling algorithmic thinking without a computer. For example students might be asked to write code to control a class-mate acting as a robot to perform a certain task. A talk by a primary school teacher on coding in the junior years had us all playing rock, paper, scissors. I’ve forgotten why, but it was great fun!

 

In the end, my take-away from the conference was to think about the best approaches for my own classes. And most particularly how to integrate all three of these approaches better. To my mind this is the best sort of take-away!

 

Bibliography

Papert, S, 1980. Mindstorms : Children, Computers, and Powerful Ideas. Basic Books. https://dl.acm.org/citation.cfm?id=1095592.

Prabhu, N.S, There Is No Best method – Why?, TESOL Quarterly, vol. 24, issue 2 (1990) pp. 161-176
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EduTech Africa 2019 – Day 2

The second day of the conference started with a series of keynotes focusing on the what, the content of education. Hayden Brown walked us through The Big History Project, an online course which looks at the history of the universe and our place in it. What struck me was the affordances offered by technology to take the curriculum to places beyond the reach of an individual teacher, but I sensed in Hayden’s story the power of a passionate teacher to make a difference.

Hadi Partovi talked about the need to teach computer science in all schools. His code.org has done amazing work in promoting coding in schools, and represents a clear imperative to address a world where computer science is increasingly important. What struck me was how obvious that seems, and how important training teachers is going to be. I am not convinced by his argument that teachers can be reskilled to teach computer science that easily. There is not just a knowledge base to be learned, but a way of thinking too, and I’m not sure a short course can do that.

The drive to address an uncertain future in which we have to prepare students for a world of work that has not been created yet remains at the forefront of everyone’s attention. How to use the tools available, not just to enhance teaching, but also to empower students as authors and creators emerges as a central theme running through many of the talks. Whether the tool is a robot, VR goggles, a 3D printer or a Google doc, the central message of the day was how to make students the authors of their own stories, the architects of their own learning.

I have to end this summary of the day with a comment I overheard at lunch, that this is all very well, but conferences like this speak to those who are already enthusiastic about tech. But what of the rest of faculty? What of teachers who shun technology? How do we include them?

I have no answer to that question. But I do believe that the pool of teachers who are enthusiastic adopters has increased exponentially, and will continue to do so. Perhaps we have already reached a critical mass, a tipping point. Many teachers are quiet adopters, who have integrated technology into their classrooms without fanfare, sufficient to their purposes. Not everyone needs to champion a cause.

A bigger question is how to extend access to schools and teachers who fall on the wrong side of the digital divide. Lack of equity comes in many forms, but the most crippling way in which inequality is reproduced is the uses to which technology is put. Some students are being taught to think critically and be creative with tech, others to capture data in a mindless way.

That, to my mind is the big question that all teachers need to address.

 
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Posted by on October 10, 2019 in Conferences, Uncategorized

 

EduTech Africa 2019 – Day 1

The tenor of this year’s conference is more subdued. Last year there was a clarion call for ending school and doing away with qualifications altogether! This year the call to transform education is rather more muted. The tone is one of quite confidence, perhaps, rather than radical fervour. The line-up of keynote speakers, of course, largely drives the tone of the conference, and voices from industry were notably absent on the first day, their place taken by teachers, by and large. The sense I get is that teachers have it under control. We’ve been playing around with how to integrate tech into our classrooms for years, and we are starting to get the hang of it!

Many of the talks I attended celebrated best practice. There is less and less advocacy every year, and more and more certainty both that technology is an important driver of change, but also that it has limits. I heard almost no voices of radical disruption, and some even voiced reminders not to throw traditional teaching methods out the window. On the floor of the exhibition hall educational publishers and the Interactive Whiteboard vendors have had to make room for a wave of robotics, 3D printers and coding solutions. Government’s move to introduce coding into the core curriculum has clearly put dollar signs in many eyes! As one who is actively looking for this kind of hardware for my grade 8s and 9s for next year, I had to force myself to look the other way. Never speak to sales reps. They all make the same claims and don’t understand pedagogy. I listened as hard as I could to my colleagues instead. So many teachers doing so many great things! We spoke about our successes, but also about our failures and dreams.

The voices raising concerns over the lack of equity, the digital divide, were also muted this year, and here I must voice my own concern. The drive to solve educational problems through technology inevitably privileges the already privileged. Our two tiered education system must not be allowed to reproduce itself this way. Teachers like myself, who work in well resourced schools have an absolute duty to pilot best practice that does not exclude by being prohibitively expensive. Government and Academia has a duty to encourage the wider adoption of this best practice. It always disturbs me when politicians open a conference and then spirit themselves away without staying to listen to the voices of the rank and file conference attendee. Sadly our deputy minister did just that, so I do hope he managed to get some listening in.

Right at the end of the day a panel of experts reflected on the effectiveness of e-learning, and the question that caught my ear was how to train the computer science teachers needed as the new plan to teach computer science to all is rolled out. CS is a discipline in its own right, and suggestions that you can retrain teachers to teach code is ludicrous. CS teaching has its own pedagogical concerns and while teachers may well, and probably should learn how to code easily, it takes training and experience to learn how to teach coding. Imagine you were thinking of retraining a cohort of Physical Education teachers to teach English, for example, and I think you’ll see what I mean. No offence intended – I certainly couldn’t teach PE to save my life! I sincerely hope that this point is understood by all stakeholders. There is still this mistaken belief out there that students are better at technology than teachers are and so kids can really teach themselves coding. Of course some can. Many of us are self-taught, but for the majority of students there is no substitute for a well trained, experienced teacher.

To my mind the tenor of the first day was all about this – the need for well trained, experienced teachers.

 
 

Using Online Citation Creators

One of the huge bugbears for students when writing essays is the whole process of in-text citation and bibliography. There are no substitutes for good old-fashioned teaching around how, and when, to use citations in text and how to go about creating a bibliography, but the collation of bibliographical information and formatting of bibliographical entries has always been problematic, for students of all ages. Thankfully there are a number of websites available, free to use, which allow you to create bibliographies with a minimum of fuss and bother. They all work in fairly similar ways, and offer similar services, usually with premium versions offering long term storage of citations, plagiarism checking and so on. It is easy enough to find a free one such as EasyBib, which you can use to generate website, book, journal and a range of other entries. Users are asked to type in the URL or title of book or journal article. The website then searches for the information and offers a suggested bibliography item. Most services allow users to add additional information not captured. You can then copy the bibliography and paste it into your essay.

To my mind the thought that students need to put into citations should be on the in-text part, rather than the formatting a bibliography part of it. Having a handy online tool liberates teacher and student to concentrate on this aspect. Most online services offer an opportunity to copy the in-text citation as well as the bibliographical entry, but I prefer to get students to do this themselves. How hard is it to extract author and date information? You also need to make sure that students are able to check what information is being generated for accuracy and update missing data where necessary. Getting students to work in pairs to do this is a good idea.

If students are using different websites, get them to rate the accuracy they achieve and make recommendations to each other.

 

Computational Thinking – a new modality of thought or just what coders do?

I want to pose a question for consideration. There is a great deal of debate and disagreement over what Computational Thinking means. For some it describes how computer scientists go about what they do, akin perhaps to the scientific method for scientists (Wolfram, 2002), and is applicable only to computer scientists. For others it is a skill set that has implications beyond the field of computer science, a set of generalizable skills of benefit to all (Wing, 2006). A third view is that it represents something of a new mode of thought capable of unique explanations (Papert, 1980) and knowledge building. In this sense it goes beyond a set of procedures, like the scientific method, and might represent a mode of thought distinct from the paradigmatic (argumentative) and narrative modes of thought proposed by Bruner (1986).

The paradigmatic mode represents knowledge founded on abstract understanding or conceptions of the world,. For example, I could explain why an apple fell to the ground by referencing the theory of gravity. This is largely the language and understanding of Science. The narrative mode of thought represents an understanding of the world founded in human interactions. I might explain why an apple fell by referencing a sequence of events in which my elbow knocked it off the table and I was not deft enough to catch it. Of course there is a continuum along which both modalities of thought intersect and interweave. So, my question is whether computational thinking represents a separate mode of thought in its own right, or simply new combinations of paradigmatic and narrative modes. If I were to model a world of apples, elbows and tables, my understanding of why apples fall might be based on a more complete understanding of how apples behave under different circumstances. The use of computational models allows for new ways of understanding the world, new ways of gaining understanding and knowledge. Chaos Theory, for example, emerged out of computational model building. Paradigmatic formulations of the world followed from computational modelling, rather than the other way round.

When we create a computational model of a weather system and run our algorithms through computers with slightly different inputs to make a hurricane path forecast, for example, or use machine learning algorithms to predict heart disease more accurately, are we deploying a new kind of thought which is somewhat different from both paradigmatic and narrative modes?

The need to ask this question rests, perhaps, on the rapid development of Machine Learning and how it threatens to disrupt our world. Machine Learning has brought us to a point where we might soon be farming most of our thinking to intelligent machines. And while probabilistic approaches to artificial intelligence allow human beings to trace back what the machine has done with our algorithms: neural networks, with their black box approaches represent thinking that is to a large extent opaque to us. It seems entirely possible then, that in the not too distant future machines will be delivering to us knowledge of the world, and we will not be able to explain the thinking behind it.

The idea of Computational Thinking (CT) has a history, and it is interesting to unpack some of it. The term was coined by Seymour Papert (1980) and popularised by Jeanette Wing (2006) and there is general consensus that it refers to the thinking skills employed by computer scientists when they are doing computer programming, derived from the cognitive processes involved when you are designing an algorithm for getting “an information-processing agent” (Cuny, et al, 2010) to find a solution to a problem. For some, information-processing agents should refer only to machines, but for others it could include human beings when they are performing computational tasks. Differences in how applicable CT is beyond computer science hinges on these nuances of understanding. I have often heard it said that getting students to design an algorithm for making a cup of tea represents CT and if students were to study designing algorithms through leaning to code they would therefore be improving their general problem solving skills.These claims are difficult to assess, but they are important because if CT applies only to the context of computer science, then its place in the curriculum occupies something of a niche, important though it might be. If, however, as claimed, it leads to benefits in general problem solving skills there is a solid case to be made for getting all students to learn programming. Equally, the case for exposing all students to some coding might rest on other claims unrelated to the transfer of CT to other domains.

Let’s start by looking at the claims made by the Coding for all lobby. Wing (2206) argued that CT skills have transferable benefits outside of computer science itself because they entail five cognitive processes, namely:

  1. Problem reformulation – reframing a problem so that it becomes solvable and familiar.
  2. Recursion – constructing a system incrementally on preceding information
  3. Decomposition – breaking the problem down into manageable bites.
  4. Abstraction – modelling the salient features of a complex system
  5. Systemic testing – taking purposeful actions to derive solutions  (Shute, et al, 2017)

Wing’s claim has received a great deal of attention and has become the bedrock for the Computer Science for All movement, the idea that all children should be exposed to CT, by teaching them to code, both because such skills will become increasingly important in an increasingly digital world, but also because they equip students for the kinds of problem solving that is increasingly important. It is debatable, though, as to whether these cognitive processes are unique to computational thought. Abstraction and decomposition, in particular, might seem to be thinking processes shared by any number of activities. Wing’s thesis that computational thinking is generalizable to all other fields could perhaps be stated in the reverse direction. Perhaps general cognitive processes are generalizable to computation? This point is not trivial, but still might not threaten the thesis that learning to code or create algorithms is excellent for developing good problem solving skills applicable to other fields.

The question of the transfer of skills gained in one context to another is, however, fraught with difficulty. Generally speaking it seems to me that knowledge and skills are gained within the framework of a particular discipline, and that the application of knowledge and skills in other contexts is always problematic to some extent. There is a close relationship between knowledge itself and what we call thinking skills. It is hard to imagine, for example, anyone possessing dispositions and thinking skills in History or Mathematics without possessing knowledge in those disciplines. As Karl Maton (2014) has pointed out, all knowledge has both knowledge and knowing structures. There is the stuff that is known and the gaze of the knower. In different fields, knowledge structures or knower structures may have greater or lesser relative importance, but one cannot distill out something which is pure knowledge, or pure knowing. Therefore the question of the transfer of skills from one context to another, from one field to another, is not a simple one. Of course we do achieve this feat. At some point in my life I learned basic numeracy skills, within the context of elementary arithmetic classes presumably, and I have been able to apply this basic knowledge and skill set to other contexts, for example computer programming. But I am not so sure that the thinking dispositions I gained while studying History at University, and my appreciation for the narrative mode of explanation are altogether much use when thinking about Computational Thinking and what I ought to be doing as a teacher of ICT skills. I am painfully aware that there are limits to the general applicability of the enquiry and data analysis skills that I learned when training to become an historian. I did not train to become a computer scientist, and therefore I am very wary of commenting on how transferable skills in computational thinking might be to contexts outside the field. But I do believe we should be wary of claims of this sort. Peter Denning (2017) has argued that the idea that all people can benefit from CT, from thinking like computer scientists, is a vague and unsubstantiated claim. For Denning, the design of algorithms (algorithmic thinking) rests not on merely setting out any series of steps, but speaks specifically to the design of steps controlling a computational model. It is context bound.

My understanding from this is that the case for teaching everyone to code cannot rest solely on an argument that CT transfers benefits. This case has yet to be proven. It does not mean that teaching coding to all is not a good thing. I believe that learning to code represents a rigorous discipline which is good for the mind, has benefits because we are living in a world where computer programs are increasingly important, and because coding involves problem solving and this too benefits the mind. All in all I think the case for teaching coding to all is extremely cogent.

I also have this sneaking suspicion that the question I posed in my opening remarks is going to be raised more and more frequently as artificial intelligence gets applied, and if so, having a population trained in some level of competence with computational thinking is probably a really good idea.

Bibliography

Bruner, J. (1986). Actual Minds, Possible Worlds. Cambridge, Mass: Harvard University Press.

Cuny, Jan,  Snyder, Larry, and Wing, Jeanette. 2010. “Demystifying Computational Thinking for Non-Computer Scientists,” work in progress.

Curzon, Paul, Tim Bell, Jane Waite, and Mark Dorling. 2019. “Computational Thinking.” In The Cambridge Handbook of Computing Education Research, edited by S.A. Fincher and A.V. Robins, 513–46. Cambridge. https://qmro.qmul.ac.uk/xmlui/bitstream/handle/123456789/57010/Curzon Computational thinking 2019 Accepted.pdf?sequence=2&isAllowed=y.

Denning, Peter J. 2017. “Remaining Trouble Spots with Computational Thinking.” Communications of the ACM 60 (6): 33–39. https://doi.org/10.1145/2998438.

Guzdial, M. 2011. “A Definition of Computational Thinking from Jeannette Wing.” Computing Education Research Blog. 2011. https://computinged.wordpress.com/2011/03/22/a-definition-of-computational-thinking-from-jeanette-wing/.

Maton, K. (2014). Knowledge and Knowers: Towards a realist sociology of education. London, UK: Routledge/Taylor & Francis Group.

Papert, Seymour. 1980. Mindstorms: Children, Computers, and Powerful Ideas. The British Journal of Psychiatry. New York: Basic Books. https://doi.org/10.1192/bjp.112.483.211-a.

Shute, Valerie J., Chen Sun, and Jodi Asbell-Clarke. 2017. “Demystifying Computational Thinking.” Educational Research Review 22 (September): 142–58. https://doi.org/10.1016/j.edurev.2017.09.003.

Wing, Jeannette. 2006. “Computational Thinking.” Communications of the ACM 49 (3): 33–35. https://doi.org/10.1145/1118178.1118215.

Wolfram, Stephen. 2002. A New Kind of Science, Wolfram Media, Inc. https://www.wolframscience.com/nks/

 

Coding & Robotics Summit – Johannesburg

Artificial Intelligence and the Fourth Industrial Revolution have become buzzwords in education, often used with little thought or understanding in slightly Pavlovian ways. There is a very real sense that big changes are afoot, and everyone is nervous about how to respond, and most particularly to be seen to be responding. I am not quite sure what to make of it, frankly. While it is clear that the working landscape will change as a result of AI, I am not convinced that much in the educational field changes … until it does. What do I mean? I think that it is already crystal clear that education should be looking to teach critical thinking, collaboration and creativity. I’m not sure that anything has changed around this. It is my belief that we should have as broad a curriculum as possible. Drama, History, Music should be as core to our curriculum as STEM. It makes no sense to me to de-emphasise or over-emphasise any field. So while I am all in favour of ensuring that coding & robotics forms part of the curriculum, I find the whole STEM, STEAM, and now STREAM (with robotics) debate counter-productive.

There will come a point, however, at which Machine Learning is powerful enough that meaningful AI applications are ready for classroom implementation. When Watson and Skinner built their teaching machines in the last century they imagined programmed learning which allowed for instant feedback and personalised learning paths, the kind of thing advocated by Pestalozzi back in the late 1700s with his one-on-one tutoring methodology. What emerged though, was the kind of drill and kill learning platforms that are the kiss of death for education. Computers are simply not intelligent enough to be able to spot when students are gaming them. However, AI does offer a possible resurrection of the idea with systems that are far more responsive and capable of analysing student production with sufficient nuance as to be useful. Real-time feedback loops enabled by devices which can read the learning brain, are not Science Fiction anymore. Nor are teaching machines which can sift the huge amount of data collected and make sense of it. There will undoubtedly, then, come a point at which AI teaching machines enter the classroom. In the lead up to that we can probably expect a range of apps that employ AI in some way, and answer particular pedagogical needs. As I get older, face and name recognition would be nice! But full-blown AI in the classroom is a little way off yet. Meaningful data analytics is probably much closer, but I’m not convinced having a wealth of data is always a good thing. I am also afraid that that data will be harvested for purposes unrelated to education. Imagine how you could Cambridge Analytica a population if you owned the data being collected on how everyone learns and thinks?

The focus of this one day conference was on Computational Thinking and on coding and robotics as a vehicle for teaching thinking skills, building the habits of mind and dispositions necessary for a post-singularity world. The South African government has recently announced that it will be introducing coding into the primary and GET phase (middle school) curricula. Karen Walstra opened affairs by walking through the history of Computational Thinking and its component parts, how coding concepts can be used across the curriculum and not just in coding classes. I am planning a blog article on Computational Thinking so I won’t dwell on it here. Her talk was vital in terms of introducing Computational Thinking, and in laying thinking skills as the foundation of any curriculum changes. However, what worries me is that an increased interest in coding has elevated it beyond what I think it is capable of providing. Computational Thinking, Coding & Robotics is not a magic bullet which will suddenly solve all education’s ills. It is a necessary skill to learn, a useful knowledge base, and a set of dispositions that all students need, but it should be seen as forming part of the thinking skills programme, not replacing the existing curriculum. All subjects and all skills are vital, in different ways. Don’t get me wrong, I am all in favour of coding’s place in the curriculum, but learning problem solving skills requires a broad world knowledge, and there are a number of thinking skills beyond the computational that are needed. Important, yes. A magic bullet, no.

St Enda’s Secondary School students designing a school website, circa 2003.

What her talk did highlight was the notion that all students can benefit from learning coding. The team from CodeJIKa presented a cogent case for this with their wonderful extra-curricular code club programme teaching students HTML, CSS and a little JavaScript. They have an online curriculum which runs largely through peer to peer learning. When I was teaching Computer Applications at St Enda’s Secondary School in the early 2000s I used the same approach. HTML & JavaScript are browser based and so do not need compilers and can be used offline – a huge consideration where Internet connection is a big problem. To my mind starting with a markup language is also helpful because it is easier to slip into, helping students get into the habit of moving between the concrete and the abstract. You can then start to slip JavaScript in quite organically and start introducing key programming concepts. Robyn Clark, from CodeJIKA, stressed how web design is also helpful in building entrepreneurial skills, giving students a side hustle. The CodeJIKA approach is to my mind a fairly easily replicable model across under-resourced schools. It is also flexible and stackable as App development, robotics and programming proper can be added as the skills and knowledge base increases. Amini Murinda from ORT South Africa presented what they have been doing in expanding coding and robotics in a growing number of schools. Both programmes clearly show that coding & robotics initiatives are engaging and transformative.

We heard from two speakers representing robotics companies, who spoke about where robotics and AI is headed, and why we should not fear job losses, and how investing in coding in primary schools could reduce failure rates in higher education. These talks provided a useful backdrop and a perspective from the world of work. I would have liked a greater emphasis on curriculum, but the summit was useful in bringing together participants from industry, teacher training and secondary and tertiary teaching sectors. It would have been great if Government had also been represented. We need many more of these discussions.

The big take-away for me was the need to take these pilot projects, together with the experience of primary and secondary teachers from the private sector who have been developing their own programmes, share best practice and work on a curriculum and pedagogies that make sense.

 

Decolonizing Computer Education – What People’s Education has to teach us.

Education in South Africa is in turmoil. In many ways our post-Apartheid educational dispensation has failed to address the problems it inherited. The big question of how to grant greater access and equity through education – perhaps best summed up by the slogan Decolonizing Education was not settled after the fall of Apartheid. Our education system is still unequal, and still largely divided along racial lines.

When I was training to become a teacher in the 1980s, the big question was some version of a Liberation Before Education or Liberation Through Education debate. Education is clearly a key component in social empowerment and social justice. The 1976 riots sprung from deep-seated unhappiness with a separate and unequal education system which taught white students blind obedience, and black students subservience. People’s Education for People’s Power emerged as a movement in response to a call by the Soweto Parents’ Crisis Committee in 1985 and a series of conferences and publications issued by the National Education Crisis Committee in 1986. Two subject committees were active in advancing content for a People’s English and People’s History curriculum. The focus was on a reformed curriculum reflecting the agency and needs of ordinary South Africans. While greater local (ie. African) content and focus was a key component of the vision, the really crucial concern was with turning knowledge into an agent for greater power and control. The history syllabus, for example was concerned not just with the study of South African history, but with a history from below approach. Using E.H. Carr’s seminal text What is History? as a basis, the NECC pushed for a rigorous and critical skill-set which would allow students to use their own, their local and national histories as a lens for developing social agency and power. People’s English, likewise, sought to use English as a means of critiquing power and empowering agency – ” to think and speak in non-racial, non-sexist and non-elitist ways” (Gardiner, n.d, p.9). The need to develop an alternative educational vision for a post-Apartheid South Africa was clear and urgent.

The South African History Archive – Images of Defiance

My first teaching job was as a teacher in a People’s Education pilot project school called Phambili in Durban in the early 1990s in the period leading up to the first democratic elections in 1994. Phambili school, a flagship of People’s Education, had two aims, to intervene in the educational crisis caused by the massive exclusion from the schooling system of students who had protested against Apartheid Education in the decade and a half after the 1976 uprising, and to pilot new democratic forms of school governance and curriculum. The school was, however, bedeviled by mismanagement and corruption by some “struggle” dignitaries. The school managed to continue thanks to a dedicated staff and board members, but faced severe lack of funding and persistent attacks from both the Apartheid State and corrupt opposition politicians who wanted to secure the building for their own personal gain. Phambili refused to go away and when I joined the staff in 1991, was struggling to resurrect itself. I was employed as an English and History teacher, and in both these faculties we tried to pilot People’s Education curricula. The English Faculty invited student representatives to join our meetings and this proved an incredibly enriching experience. As a Matric teacher there was not much I could do to change the setworks studied, but I Africanised the unseen setworks and comprehension passages chosen. In my first week of teaching I was challenged by my Matric 10B class on the whole question of why we studied Shakespeare. I hummed and hawed a bit, said a few things about universal human values, and the need to study the canon, but I could see the class was unconvinced. Luckily for me that weekend an article appeared in the Sunday newspapers about Chris Hani, leader of the Communist Party and liberation hero, who said how much he admired Shakespeare and had studied him in the guerilla camps in Tanzania. I cut it out and pinned it to my door. Not only did opposition to studying Shakespeare disappear, but my classroom was renamed Chris Hani Base Camp. I had clearly passed some kind of test.

The way that we came to theorize what people’s English looked like at Phambili was founded on our notion of agency. I was not aware of the works of Mikhail Bakhtin at that time, but the sense of the need to give our students access to the literacies and knowledges of power while at the same time developing the power of their own voice was central. This deeply dialogic notion foregrounds the agency of student voices while recognising that hegemonic literacies and discourses need to be mastered.

The History faculty used the NECC published textbook What is History? as its central text, but I believe we built a strong sense of history from below as a critical tool for confronting power. Poor historians make poor revolutionaries could have been our mantra. Things came to a head at a History teachers’ conference at the University of Natal where plans for a new History syllabus were unveiled which directly conflicted with our notion of People’s Education. The syllabus seemed to us to be triumphalist. History was to become the story of the ANC’s rise to power, much as history under the National Party had been subservient to political propaganda. We agitated from the floor, and were eventually granted an audience with John Pampallis. When the new curriculum was eventually unveiled, after the elections in 1994, very little remained of people’s Education.

And that I think is the problem. Subsequent revisions of the curriculum were to incorporate an extreme version of Outcomes Based Education, a somewhat reactionary and behaviourist educational philosophy, which was opaque and technicist and views education as the mastery of discrete skills. Although, clearly, much has changed for the better, our education system remains a two-tiered system replicating inequality and stifling agency. The sense of liberation through education that people’s Education engendered has all but disappeared and the focus is now on South Africa’s failing matriculation pass rate and position at the bottom of the international league tables. The current cry to decolonize education can only be seen as an indictment of the failures to implement an education system that meaningfully addresses the inequalities of the past. We need a return to the People’s Education agenda.

So, what would a People’s Computer Education curriculum look like? Computing represents a literacy of power, increasingly so as our lives become dominated by digital technologies. I would argue that computing education needs to empower students and promote agency both by giving students access to these voices of power, but also by empowering the power of students’ voice, their ability to express their creativity and ideas through digital media. Robert Reich (1992) has argued that the new Information Economy is reproduced by a two-tiered education system that produces a labour force of data capturers on the one hand, and a managerial class of information/symbol manipulators on the other. As computer educators we need to ensure that we are giving all our students access to the skills and dispositions which will enable them as digital masters rather than merely hewers of wood and carriers of water in the new digital economy. If we teach spreadsheets it should not just be about the how, it also needs to be about the why, it needs to prepare students for entrepreneurship and creativity. If we teach coding, it should not be just so that students can write some code, it needs to encompass a vision of a humanity that can rise above the challenge of Artificial Intelligence, that has a purpose and dream, that has a destiny.

I realise that this formulation is hopelessly Romantic, but I am an optimist and I believe we need to teach hope, and inspire our students to be the masters of their own lives. Ultimately Computing from below is the story of a new humanism that rejects a society that is mechanical and technocratic, but sees technology as an extension of the human will to survive and thrive. Ultimately People’s Computing needs to teach students to see a society in which they can use digital technologies to advance their lives and build a world that is non-classist, non-sexist and non-racist.

Bibliography

Gardner, M, (n.d) Transforming Itself: People’s Education for people’s Power and Society in South Africa. Accessed https://www.sahistory.org.za/sites/default/files/archive-files2/remar87.5.pdf

Reich, R. (1992). The Work of Nations: Preparing Ourselves for 21st Century Capitalism. New York: Vintage Books. Retrieved from https://www.amazon.com/Work-Nations-Preparing-Ourselves-Capitalis-ebook/dp/B004CFAW7A 

The South African History Archive. http://www.saha.org.za/imagesofdefinace/10_fighting_years_1976_1986_peoples_education_for_peoples_power.htm

 
 
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