Ending the Milling Mindset
Posted: November 17, 2014 Filed under: Education, Opinion | Tags: advocacy, authenticity, community, curriculum, design, education, educational problem, educational research, ethics, failure rate, grand challenge, higher education, in the student's head, learning, measurement, reflection, resources, student perspective, students, teaching, teaching approaches, thinking, tools, universal principles of design 7 CommentsThis is the second in a set of posts that are critical of current approaches to education. In this post, I’m going to extend the idea of rejecting an industrial revolutionary model of student production and match our new model for manufacturing, additive processes, to a new way to produce students. (I note that this is already happening in a number of places, so I’m not claiming some sort of amazing vision here, but I wanted to share the idea more widely.)
Traditional statistics is often taught with an example where you try to estimate how well a manufacturing machine is performing by measuring its outputs. You determine the mean and variation of the output and then use some solid calculations to then determine if the machine is going to produce a sufficient number of accurately produced widgets to keep your employers at WidgetCo happy. This is an important measure for things such as getting the weight right across a number of bags of rice or correctly producing bottles that hold the correct volume of wine. (Consumers get cranky if some bags are relatively empty or they have lost a glass of wine due to fill variations.)
If we are measuring this ‘fill’ variation, then we are going to expect deviation from the mean in two directions: too empty and too full. Very few customers are going to complain about too much but the size of the variation can rarely be constrained in just one direction, so we need to limit how widely that fill needle swings. Obviously, it is better to be slightly too full (on average) than too empty (on average) although if we are too generous then the producer loses money. Oh, money, how you make us think in such scrubby, little ways.
When it comes to producing items, rather than filling, we often use a machine milling approach, where a block of something is etched away through mechanical or chemical processes until we are left with what we want. Here, our tolerance for variation will be set based on the accuracy of our mill to reproduce the template.
In both the fill and the mill cases, imagine a production line that travels on a single pass through loading, activity (fill/mill) and then measurement to determine how well this unit conforms to the desired level. What happens to those items that don’t meet requirements? Well, if we catch them early enough then, if it’s cost effective, we can empty the filled items back into a central store and pass them through again – but this is wasteful in terms of cost and energy, not to mention that contents may not be able to be removed and then put back in again. In the milling case, the most likely deviance is that we’ve got the milling process wrong and taken away things in the wrong place or to the wrong extent. Realistically, while some cases of recycling the rejects can occur, a lot of rejected product is thrown away.
If we run our students as if they are on a production line along these lines then, totally unsurprisingly, we start to set up a nice little reject pile of our own. The students have a single pass through a set of assignments, often without the ability to go and retake a particular learning activity. If they fail sufficient of these tests, then they don’t meet our requirements and they are rejected from that course. Now some students will over perform against our expectations and, one small positive, they will then be recognised as students of distinction and not rejected. However, if we consider our student failure rate to reflect our production wastage, then failure rates of 20% or higher start to look a little… inefficient. These failure rates are only economically manageable (let us switch off our ethical brains for a moment) if we have enough students or they are considered sufficiently cheap that we can produce at 80% and still make money. (While some production lines would be crippled by a 10% failure rate, for something like electric drive trains for cars, there are some small and cheap items where there is a high failure rate but the costing model allows the business to stay economical.) Let us be honest – every University in the world is now concerned with their retention and progression rates, which is the official way of saying that we want students to stay in our degrees and pass our courses. Maybe the single pass industrial line model is not the best one.
Why carve back to try to reveal people, when we could build people up instead?
Enter the additive model, via the world of 3D printing. 3D printing works by laying down the material from scratch and producing something where there is no wastage of material. Each item is produced as a single item, from the ground up. In this case, problems can still occur. The initial track of plastic/metal/material may not adhere to the plate and this means that the item doesn’t have a solid base. However, we can observe this and stop printing as soon as we realise this is occurring. Then we try again, perhaps using a slightly different approach to get the base to stick. In student terms, this is poor transition from the school environment, because nothing is sticking to the established base! Perhaps the most important idea, especially as we develop 3D printing techniques that don’t require us to deposit in sequential layers but instead allows us to create points in space, is that we can identify those areas where a student is incomplete and then build up that area.
In an additive model, we identify a deficiency in order to correct rather than to reject. The growing area of learning analytics gives us the ability to more closely monitor where a student has a deficiency of knowledge or practice. However, such identification is useless unless we then act to address it. Here, a small failure has become something that we use to make things better, rather than a small indicator of the inescapable fate of failure later on. We can still identify those students who are excelling but, now, instead of just patting them on the back, we can build them up in additional interesting ways, should they wish to engage. We can stop them getting bored by altering the challenge as, if we can target knowledge deficiency and address that, then we must be able to identify extension areas as well – using the same analytics and response techniques.
Additive manufacturing is going to change the way the world works because we no longer need to carve out what we want, we can build what we want, on demand, and stop when it’s done, rather than lamenting a big pile of wood shavings that never amounted to a table leg. A constructive educational focus rejects high failure rates as being indicative of missed opportunities to address knowledge deficiencies and focuses on a deep knowledge of the student to help the student to build themselves up. This does not make a course simpler or drop the quality, it merely reduces unnecessary (and uneconomical) wastage. There is as much room for excellence in an additive educational framework – if anything, you should get more out of your high achievers.
We stand at a very interesting point in history. It is time to revisit what we are doing and think about what we can learn from the other changes going on in the world, especially if it is going to lead to better educational results.
Knowing the Tricks Helps You To Deal With Assumptions
Posted: September 10, 2014 Filed under: Education | Tags: authenticity, blogging, card shouting, collaboration, community, curriculum, data visualisation, design, education, educational problem, educational research, Heads Heads, higher education, Law of Small Numbers, random numbers, random sequence, random sequences, randomness, reflection, resources, students, teaching, teaching approaches, tools Leave a commentI teach a variety of courses, including one called Puzzle-Based Learning, where we try to teach think and problem-solving techniques through the use of simple puzzles that don’t depend on too much external information. These domain-free problems have most of the characteristics of more complicated problems but you don’t have to be an expert in the specific area of knowledge to attempt them. The other thing that we’ve noticed over time is that a good puzzle is fun to solve, fun to teach and gets passed on to other people – a form of infectious knowledge.
Some of the most challenging areas to try and teach into are those that deal with probability and statistics, as I’ve touched on before in this post. As always, when an area is harder to understand, it actually requires us to teach better but I do draw the line at trying to coerce students into believing me through the power of my mind alone. But there are some very handy ways to show students that their assumptions about the nature of probability (and randomness) so that they are receptive to the idea that their models could need improvement (allowing us to work in that uncertainty) and can also start to understand probability correctly.
We are ferociously good pattern matchers and this means that we have some quite interesting biases in the way that we think about the world, especially when we try to think about random numbers, or random selections of things.
So, please humour me for a moment. I have flipped a coin five times and recorded the outcome here. But I have also made up three other sequences. Look at the four sequences for a moment and pick which one is most likely to be the one I generated at random – don’t think too much, use your gut:
- Tails Tails Tails Heads Tails
- Tails Heads Tails Heads Heads
- Heads Heads Tails Heads Tails
- Heads Heads Heads Heads Heads
Have you done it?
I’m just going to put a bit more working in here to make sure that you’ve written down your number…
I’ve run this with students and I’ve asked them to produce a sequence by flipping coins then produce a false sequence by making subtle changes to the generated one (turns heads into tails but change a couple along the way). They then write the two together on a board and people have to vote on which one is which. As it turns out, the chances of someone picking the right sequence is about 50/50, but I engineered that by starting from a generated sequence.
This is a fascinating article that looks at the overall behaviour of people. If you ask people to write down a five coin sequence that is random, 78% of them will start with heads. So, chances are, you’ve picked 3 or 4 as you’re starting sequence. When it comes to random sequences, most of us equate random with well-shuffled, and, on the large scale, 30 times as many people would prefer option 3 to option 4. (This is where someone leaps into the comments to say “A-ha” but, it’s ok, we’re talking about overall behavioural trends. Your individual experience and approach may not be the dominant behaviour.)
From a teaching point of view, this is a great way to break up the concepts of random sequences and some inherent notion that such sequences must be disordered. There are 32 different ways of flipping 5 coins in a strict sequence like this and all of them are equally likely. It’s only when we start talking about the likelihood of getting all heads versus not getting all heads that the aggregated event of “at least one head” starts to be more likely.
How can we use this? One way is getting students to write down their sequences and then asking them to stand up, then sit down when your ‘call’ (from a script) goes the other way. If almost everyone is still standing at heads then you’ve illustrated that you know something about how their “randomisers” work. A lot of people (if your class is big enough) should still be standing when the final coin is revealed and this we can address. Why do so many people think about it this way? Are we confusing random with chaotic?
The Law of Small Numbers (Tversky and Kahneman), also mentioned in the post, which is basically that people generalise too much from small samples and they expect small samples to act like big ones. In your head, if the grand pattern over time could be resorted into “heads, tails, heads, tails,…” then small sequences must match that or they just don’t look right. This is an example of the logical fallacy called a “hasty generalisation” but with a mathematical flavour. We are strongly biassed towards the the validity of our experiences, so when we generate a random sequence (or pick a lucky door or win the first time at poker machines) then we generalise from this small sample and can become quite resistant to other discussions of possible outcomes.
If you have really big classes (367 or more) then you can start a discussion on random numbers by asking people what the chances are that any two people in the room share a birthday. Given that there are only 366 possible birthdays, the Pigeonhole principle states that two people must share a birthday as, in a class of 367, there are only 366 birthdays to go around so one must be repeated! (Note for future readers: don’t try this in a class of clones.) There are lots of other, interesting thinking examples in the link to Wikipedia that helps you to frame randomness in a way that your students might be able to understand it better.
10 pigeons into 9 boxes? Someone has a roommate.
I’ve used a lot of techniques before, including the infamous card shouting, but the new approach from the podcast is a nice and novel angle to add some interest to a class where randomness can show up.
I have a new book out: A Guide to Teaching Puzzle-based learning. #puzzlebasedlearning #education
Posted: September 5, 2014 Filed under: Education, Opinion | Tags: blogging, colleagues, curriculum, design, Ed Meyer, education, educational problem, Generation Why, higher education, in the student's head, raja sooriamurthi, reflection, resources, shameless self-promotion, student perspective, students, teaching, teaching approaches, thinking, universal principles of design, work/life balance, workload, Zbyszek Michalewicz Leave a commentTime for some pretty shameless self-promotion. Feel free to stop reading if that will bother you.
My colleagues, Ed Meyer from BWU, Raja Sooriamurthi from CMU and Zbyszek Michalewicz (emeritus from my own institution) and I have just released a new book, called “A Guide to Teaching Puzzle-based learning.” What a labour of love this has been and, better yet, we are still still talking to each other. In fact, we’re planning some follow-up events next year to do some workshops around the book so it’ll be nice to work with the team again.
(How to get it? This is the link to Springer, paperback and e-Book. This is the link to Amazon, paperback only I believe.)
Here’s a slightly sleep-deprived and jet-lagged picture of me holding the book as part of my “wow, it got published” euphoria!
See how happy I am? And also so out of it.
The book is a resource for the teacher, although it’s written for teachers from primary to tertiary and it should be quite approachable for the home school environment as well. We spent a lot of time making it approachable, sharing tips for students and teachers alike, and trying to get all of our knowledge about how to teach well with puzzles down into the one volume. I think we pretty much succeeded. I’ve field-tested the material here at Universities, schools and businesses, with very good results across the board. We build on a good basis and we love sound practical advice. This is, very much, a book for the teaching coalface.
It’s great to finally have it all done and printed. The Springer team were really helpful and we’ve had a lot of patience from our commissioning editors as we discussed, argued and discussed again some of the best ways to put things into the written form. I can’t quite believe that we managed to get 350 pages down and done, even with all of the time that we had.
If you or your institution has a connection to SpringerLink then you can read it online as part of your subscription. Otherwise, if you’re keen, feel free to check out the preview on the home page and then you may find that there are a variety of prices available on the Web. I know how tight budgets are at the moment so, if you do feel like buying, please buy it at the best price for you. I’ve already had friends and colleagues ask what benefits me the most and the simple answer is “if people read it and find it useful”.
To end this disgraceful sales pitch, we’re actually quite happy to run workshops and the like, although we are currently split over two countries (sometimes three or even four), so some notice is always welcome.
That’s it, no more self-promotion to this extent until the next book!
ITiCSE 2014, Day 3, Session 7B, Peer Instruction, #ITiCSE2014 #ITiCSE
Posted: June 25, 2014 Filed under: Education | Tags: community, computer science education, curriculum, design, education, educational problem, educational research, flipped classroom, higher education, in the student's head, inverted classroom, ITiCSE, ITiCSE 2014, learning, peer instruction, teaching, teaching approaches, thinking Leave a commentThe first talk was “Peer Instruction: a Link to the Exam” presented by Daniel Zingaro from University of Toronto. Peer Instruction (PI) is an active learning pedagogy developed for physics and now heavily used in computing. Students complete a reading quiz prior to class and teachers use multiple-choice quizzes to assess knowledge. (You can look this one up in a number of places but I’ve discussed it here before a bit.) There’s a lot of research that shows gains between individual and group vote, with enduring improvements in student learning. (We can use isomorphic questions to reduce the likelihood of copying.) Both students and instructors value the learning.
PI appears to demonstrate improved learning outcomes on the final exam grades, as well as perceived depth of learning. (Couple of studies here from Beth Simon et al, and Daniel himself, checking Beth’s results.) But what leads to this improved outcome? The peer discussion. The class wide discussion? Both? If one part isn’t useful then we can adapt it to make it more useful to Computer Scientists. Daniel is going to use isomorphic questions to investigate relationships between PI components and final exam grades.
The isomorphic questions test the same concept with different questions, where if they get the first one right, we hope that they get the second one right – and if people learn how to do one, then that knowledge flows on to the other. (The example given was of loop complexity in nested loops depending on different variables.)
Daniel has two question modes in this experiment, which are slightly different. Both modes include the PI components, but the location of the isomorphic questions vary between the two approaches in the second question. In the Peer ℗ mode, the isomorphic question comes directly after the group vote and the second mode (Combined – C), the Q2 isomorphic questions occur direct after the instructor has had a chance to influence the class.
Are the questions really isomorphic and of the same difficulty? An external ranker was used to verity this and then the question pairs and mode were randomised. The difficulty of the questions was found to be statistically equivalent, based on the percentage of Q1 that were found to be correct.
Daniel had two hypotheses. Firstly, that peer scores will correlate to final exam scores. Secondly, that combined scores will also correlate with final exam scores, but the correlation should be stronger than for Peer, with the Combined questions representing learning from the full PI cycle. In terms of the final exam, there were three measures of the final exam grades: total exam score, score on the tracing question (similar to PI questions) and score on a code-writing question (very different to PI questions).
The implementation was a CS1 course with 3 lectures/week, with reading quizzes worthy 4% submitted prior to each lecture, clicker responses worth 5%, where the lectures on average contained three PI cycles- one cycle per lecture contained the follow-up isomorphic question. Multiple regression was used to test relationships between PI and final exam scores.
All of the results were statistically significant. For code-tracing, hat students know before exam explains 13% of their scores in the final exam. With the peer questions, it goes up to 16%. With combined as well, it goes up to 19%. Is this practically significant? Daniel raised this question because it doesn’t rise very much.
In terms of code writing, Baseline is 16%, + Peers is 22% and +Combined is 25%, so we’re starting to see more contribution from peers than instructor in this case. Are we measuring the different difficulty of a problem that peers couldn’t correct, which is why the instructor does less?
Overall? Baseline 21%, Peer 30% and then Combined is 34%. (Any questions about the stats, please read the paper. 🙂 )
Maybe adding combined questions to peer questions increases our predictive accuracy, just because we’re adding more data and this being able to produce a better model?
In discussion, PI performance related to final exam scores (as expected). Peer learning alone is important and the instructor-led discussion is important, over and above peer learning. This validates the role of the instructor in a “student-centred” classroom. Given that PI uses MCQs, we might expect it to only correlate with code-tracing but it does appear to correlate with code-writing problems as well – there may be deep conceptual similarities between PI questions and programming skills. But would the students that learned from PI also the students that would have learned from any other form of instruction? Still an open question and there’s a lot of ongoing work still to do.
The next paper was “Comparing Outcomes in Inverted and Traditional CS1” presented by Diane Horton from U Toronto. I’ve been discussing early intervention and student attendance issues in inverted/hybrid courses with Jennifer Campbell and Michelle Craig, also from U Toronto and also on this paper, as part of an attempt to get some good answers so I’d just come straight out of a lunch, discussing inverted classrooms and their outcomes. (Again, this is why we come to conferences – much of the value is in the meetings and discussion that are just so hard to have when you’re doing your day job or fitting a Skype meeting into the wee small hours to bridge the continental time gap.)
As a reminder, in inverted teaching, some or all of the material is delivered outside the classroom. Work typically done as homework is done in the lecture with the help of instructor or TAs. There were three research questions. Would the inverted offerings have better outcomes? Would inverted teaching affect students’ behaviour or experience? Would particular subgroups respond differently, especially English-language learners and beginner programmers?
The CS1 course at Toronto is a 12 week course in Python, objects-early, classes-late, with most students in 1st year and less than half looking to major in CS. The lectures are roughly 200 students, with 5 of these lecture sections.
Before the lecture, students prepared by watching videos, from the instructors, mostly screencasts of live programming with voice over, credit for attempting quizzes embedded in videos is 0.5% per week. (It’s scary how small that fraction has to be and really rather sad, from a behavioural perspective.)
During the lecture, the instructors used a worked example and students worked on worksheet-based exercises for most of the lectures, with assistance, solo or in pairs. This was a responsive teaching approach because the instructor could draw the class together as required. There was no mark reward or penalty that depended on attendance. If you were solid on the material, it was okay to miss the lecture. The mark scheme reflected some marks for lecture preparation with an increased number of online exercises and decreased weighting on labs.
The inverted CS1 course had gone well in the pilot in January 2013, which was published in a peer at SIGCSE ’14, but it was hard to compare this with the previous class as the make-up of the cohort varies from September to January courses. The study was run again in a more similar cohort in September 2014. The data presented here is for a similar cohort with a high overlap of instructors, compared the traditional offering.
For the present study, there were pre- and post-course surveys about attitude and behaviour, competed on-paper in the lecture. Weekly lecture attendance counts were made and standard university course valuations collected. In terms of attendance, the inverted pilot was the lowest, but the inverted class had lower attendance most of the time – an effect that we have also seen under some circumstances and are still thinking about. Interestingly, students thought that the inverted lectures weren’t seen as being as useful as face-to-face lectures but the online support materials were seen to be very helpful. As a package, this seems to be an overall positive experience.
The hypothesis was that students in the inverted offering would self-report a higher quality of learning experience and greater enjoyment but this wasn’t supported in the data, nor was it for beginners in particular. However, when asked if they wanted more inverted courses, there was a very strong positive response to this question.
The authors expected that beginners would benefit more because they need more helps and the gap between beginners and experiences students would reduce – this wasn’t supported by the data. Also, there was no reduction of gaps for English language learners, either.
Would the inverted course help people stay on and pass the course? Well, however success was defined, the pass rate was remarkably consistent, even when the beginners were isolated. However, it does appear that the overall level of knowledge, as measured by the final exam grades, actually improved in the inverted offerings, across two exams of similar difficult, with a jump from an average grade of 66% to 74% between the terms. Is this just due to the inverted teaching?
Maybe students learned more in the inverted offering because they spent more time on task? Based on self-reported student time, this doesn’t appear to be true. Maybe the beginners got killed off early to reduce their numbers and raise the mark? No, the drop rates among beginners were the same. It appears that the 8 percentage point increase may be related to the inverted mode, although, obviously, more work is required.
Is it worth it? They used no additional TA resources but the development time was enormous. You may not be ready for this investment. There are other options, you don’t need to use videos and you can use pre-existing materials to reduce costs.
Future work involves looking at dropping patterns – who drops when – and student who stumble and recover. They’re also looking at a full online CS1 course for course credit.
The final talk was on “Making Group Processes Explicit to Students: A Case for Justice” presented by Ville Isomöttönen. Project courses have a very long history in Computer Science, as capstones, using authentic customer projects, and the intention is to provide a realistic experience. (Editor’s note: It’s worth noting that some of this may be coming from the “We got punished like this so you can be too.”) What do students actually learn from this? Are they learning what we want them to learn or they are learning something very different and, potentially, much darker?
(This sounds like the kind of philosophical paper I’d give, let’s see where it goes! 🙂 )
If we have tertiary students, why can’t we just place them into a workplace for work experience? They’re adults – maybe we can separate this aspect and the pedagogue. The author’s study wants to look at how to promote conceptual learning in the response of realistic course work. Parker (1999) proposes that students are spending their effort of building wiring products, rather than actually learning about and reflecting upon the professional issues we consider important. The conjecture is that just because the situation is realistic doesn’t mean that the conceptual learning is happening as we intended.
The study is based around a fairly straight forward project-based learning structure, but had a Pass/Fail grade, with no distinction grading as far as I could tell. The teaching was baed on weekly group discussions, with self/peer evaluations, also housed in a group situation, and technical supervision offered by teaching assistant. Throughout the course, students are prompted to think about their operation at a conceptual level. Hmm. I’m not sure what the speaker means by this as, without a very detailed description of what is going on, this could have many different implementations.
We then cut to a diagram of justice conceptualised – I may have missed something as I’m not quite sure how this sits with the group work. I can’t find the diagram online but it involves participation, involving and negotiating with others – fused together as the skill of justice. This sits above statuses, norms and roles. Some of the related work deals with fairness (Richards 2009) as a key attribute of successful group work, Clear 2002 uses it in diagnostic technique, and Pieterse and Thompson 2010 mentioned ‘social loafers’ and ‘diligent isolates’.
I’m dreadfully sorry, dear reader, but I’m not following this properly so this may be a bit sketchy. Go and read the paper and I’ll try to get this together. Everyone else in the room appears to be getting this so I may just be tired or struggling with my (not very good) hearing and someone who is speaking rather quietly.
The underlying pedagogy comes from the social realist mindset (Moore,2000, Maton and Moore, 2010) and “avoids the dilemma between constructivist relativism and positivist absolutism”. We should also look at the Integrative Pedagogy (Tynjana (sp)), where the speaker feels that what they are describing is a realist version of this.
The course was surveyed with a preliminary small study (N=21/26, which is curious. Which one is it? Ah, 21 out of 26 enrolled, there we go.). The survey questions were… rather loose and very open to influence, unfortunately, from my quick glance at them but I will have to read the original paper.
Justice is a difficult topic to address, especially where it’s reified as a professional skill that can be developed, and discussing the notion of justice in terms of the ways that a group can work together fairly is very important. I suppose I’m not 100% convinced how much is added in this context through the use of a new term that is an apparent parent to communication and negotiation, with the desired outcome of fairness, because the amalgamation seems to obscure the individual components that would be improved upon to return to a fair state. The very small study, and a small survey, is a valid approach for a case study or phenomenographic approach, but I get the feeling that I was seeing a grounded theory argument. We do have to expose our desired processes to students if we’re going to achieve cognitive apprenticeship and there is a great deal of tension between industrial practice and key concepts, so this is a very interesting area to work in. I completely agree with the speaker that our heavy technical focus often precludes discussions of the empathic, philosophical and intangible, but I’m yet to see how this approach contributes.
The discussions mentioned as important are very important but group reports and discussion are a built-in part of many SE process models so I wonder how the justice theme amplifies this aspects. Again, getting students to engage in a dialogue that they do not expect to have in CS can be very challenging but we could be discussing issues such as critical thinking and ethics, which are often equally alien and orthogonal to the technical, without forming a compound concept that potentially obscures the underlying component mechanisms.
Simon asked a very good question: you didn’t present anything that showed a problem where the students would have needed the concept of justice. Apparently, this is in the writings that are yet to be analysed. The answer to the question ended up as an unlabelled graph on the blackboard which was focused on a skill difference with more experienced peers. I still can’t see how justice ties into this. I have to go and get my hearing checked.
ITiCSE 2014, Session 3C: Gender and Diversity, #ITiCSE2014 #ITiCSE @patitsel
Posted: June 24, 2014 Filed under: Education | Tags: advocacy, authenticity, community, computer science, design, education, educational problem, educational research, Elizabeth Patitsas, equality, ethics, gender roles, higher education, ITiCSE, ITiCSE 2014, learning, mentoring, sexism, sexism in computer science, students, teaching approaches, thinking 1 CommentThis sessions was dedicated to the very important issues of gender and diversity. The opening talk in this session was “A Historical Examination of the Social Factors Affecting Female Participation in Computing”, presented by Elizabeth Patitsas (@patitsel). This paper was a literature review of the history of the social factors affecting the old professional association of the word “computer” with female arithmeticians to today’s very male computing culture. The review spanned 73 papers, 5 books, 2 PhD theses and a Computing Educators Oral History project. The mix of sources was pretty diverse. The two big caveats were that it only looked at North America (which means that the sources tend to focus on Research Intensive universities and white people) and that this is a big picture talk, looking at social forces rather than individual experiences. This means that, of course, individuals may have had different experiences.
The story begins in the 19th Century, when computer was a job and this was someone who did computations, for scientists, labs, or for government. Even after first wave feminism, female education wasn’t universally available and the women in education tended to be women of privilege. After the end of the 19th century, women started to enter traditional universities to attempt to study PhDs (although often receiving a Bachelors for this work) but had few job opportunities on graduation, except teaching or being a computer. Whatever work was undertaken was inherently short-term as women were expected to leave the work force on marriage, to focus on motherhood.
During the early 20th Century, quantitative work was seen to be feminine and qualitative work required the rigour of a man – things have changed in perceptions, haven’t they! The women’s work was grunt work: calculating, microscopy. Then there’s men’s work: designing and analysing. The Wars of the 20th Century changed this by removing men and women stepping into the roles of men. Notably, women were stereotyped as being better coders in this role because of their computer background. Coding was clerical, performed by a woman under the direction of a male supervisor. This became male typed over time. As programming became more developed over the 50s and 60s and the perception of it as a dark art started to form a culture of asociality. Random hiring processes started to hurt female participation, because if you are hiring anyone then (quitting the speaker) if you could hire a man, why hire a woman? (Sound of grinding teeth from across the auditorium as we’re all being reminded of stupid thinking, presented very well for our examination by Elizabeth.)
CS itself stared being taught elsewhere but became its own school-discipline in the 60s and 70s, with enrolment and graduation of women matching that of physics very closely. The development of the PC and its adoption in the 80s changed CS enrolments in the 80s and CS1 became a weeder course to keep the ‘under qualified’ from going on to further studies in Computer Science. This then led to fewer non-traditional CS students, especially women, as simple changes like requiring mathematics immediately restricted people without full access to high quality education at school level.
In the 90s, we all went mad and developed hacker culture based around the gamer culture, which we already know has had a strongly negative impact on female participation – let’s face it, you don’t want to be considered part of a club that you don’t like and goes to effort to say it doesn’t welcome you. This led to some serious organisation of women’s groups in CS: Anita Borg Institute, CRA-W and the Grace Hopper Celebration.
Enrolments kept cycling. We say an enrolment boom and bust (including greater percentage of women) that matched the dot-com bubble. At the peak, female enrolment got as high as 30% and female faculty also increased. More women in academia corresponded to more investigation of the representation of women in Computer Science. It took quite a long time to get serious discussions and evidence identifying how systematic the under-representation is.
Over these different decades, women had very different experiences. The first generation had a perception that they had to give up family, be tough cookies and had a pretty horrible experience. The second generation of STEM, in 80s/90s, had female classmates and wanted to be in science AND to have families. However, first generation advisers were often very harsh on their second generation mentees as their experiences were so dissimilar. The second generation in CS doesn’t match neatly that of science and biology due to the cycles and the negative nerd perception is far, far stronger for CS than other disciplines.
Now to the third generation, starting in the 00s, outperforming their male peers in many cases and entering a University with female role models. They also share household duties with their partners, even when both are working and family are involved, which is a pretty radical change in the right direction.
If you’re running a mentoring program for incoming women, their experience may be very. very different from those of the staff that you have to mentor them. Finally, learning from history is essential. We are seeing more students coming in than, for a number of reasons, we may be able to teach. How will we handle increasing enrolments without putting on restrictions that disproportionately hurt our under-represented groups? We have to accept that most of our restrictions actually don’t apply in a uniform sense and that this cannot be allowed to continue. It’s wrong to get your restrictions in enrolment at a greater expense on one group when there’s no good reason to attack one group over another.
One of the things mentioned is that if you ask people to do something because of they are from group X, and make this clear, then they are less likely to get involved. Important note: don’t ask women to do something because they’re women, even if you have the intention to address under-representation.
The second paper, “Cultural Appropriation of Computational Thinking Acquisition Research: Seeding Fields of Diversity”, presented by Martha Serra, who is from Brazil and good luck to them in the World Cup tonight! Brazil adapted scalable game design to local educational needs, with the development of a web-ased system “PoliFacets”, seeding the reflection of IT and Educational researchers.
Brazil is the B in BRICS, with nearly 200 million people and the 5th largest country in the World. Bigger than Australia! (But we try harder.) Brazil is very regionally diverse: rain forest, wetlands, drought, poverty, Megacities, industry, agriculture and, unsurprisingly, it’s very hard to deal with such diversity. 80% of youth population failed to complete basic education. Only 26% of the adult population reach full functional literacy. (My jaw just dropped.)
Scalable Game Design (SGD) is a program from the University of Colorado in Boulder, to motivate all students in Computer Science through game design. The approach uses AgentSheets and AgentsCubes as visual programming environments. (The image shown was of a very visual programming language that seemed reminiscent of Scratch, not surprising as it is accepted that Scratch picked up some characteristics from AgentSheets.)
The SGD program started as an after-school program in 2010 with a public middle school, using a Geography teacher as the program leader. In the following year, with the same school, a 12-week program ran with a Biology teacher in charge. Some of the students who had done it before had, unfortunately, forgotten things by the next year. The next year, a workshop for teachers was introduced and the PoliFacets site. The next year introduced more schools, with the first school now considered autonomous, and the teacher workshops were continued. Overall, a very positive development of sustainable change.
Learners need stimulation but teachers need training if we’re going to introduce technology – very similar to what we learned in our experience with digital technologies.
The PolFacets systems is a live documentation web-based system used to assist with the process. Live demo not available as the Brazilian corner of internet seems to be full of football. It’s always interesting to look at a system that was developed in a different era – it makes you aware how much refactoring goes into the IDEs of modern systems to stop them looking like refugees from a previous decade. (Perhaps the less said about the “Mexican Frogger” game the better…)
The final talk (for both this session and the day) was “Apps for Social Justice: Motivating Computer Science Learning with Design and Real-World Problem Solving”, presented by Sarah Van Wart. Starting with motivation, tech has diversity issues, with differential access and exposure to CS across race and gender lines. Tech industry has similar problems with recruiting and retaining more diverse candidates but there are also some really large structural issues that shadow the whole issue.
Structurally, white families have 18-20 times the wealth of Latino and African-American people, while jail population is skewed the opposite way. The schools start with the composition of the community and are supposed to solve these distribution issues, but instead they continue to reflect the composition that they inherited. US schools are highly tracked and White and Asian students tend to track into Advanced Placement, where Black and Latino students track into different (and possibly remedial) programs.
Some people are categorically under-represented and this means that certain perspectives are being categorically excluded – this is to our detriment.
The first aspect of the theoretical prestige is Conceptions of Equity. Looking at Jaime Escalante, and his work with students to do better at the AP calculus exam. His idea of equity was access, access to a high-value test that could facilitate college access and thus more highly paid careers. The next aspect of this was Funds of Knowledge, Gonzalez et al, where focusing on a white context reduces aspects of other communities and diminishes one community’s privilege. The third part, Relational Equity (Jo Boaler), reduced streaming and tracking, focusing on group work, where each student was responsible for each student’s success. Finally,Rico Gutstein takes a socio-political approach with Social Justice Pedagogy to provide authentic learning frameworks and using statistics to show up the problems.
The next parts of the theoretical perspective was Computer Science Education, and Learning Sciences (socio-cultrual perspective on learning, who you are and what it means to be ‘smart’)
In terms of learning science, Nasir and Hand, 2006, discussed Practice-linked Identities, with access to the domain (students know what CS people do), integral roles (there are many ways to contribute to a CS project) and self-expression and feeling competent (students can bring themselves to their CS practice).
The authors produced a short course for a small group of students to develop a small application. The outcome was BAYP (Bay Area Youth Programme), an App Inventor application that queried a remote database to answer user queries on local after-school program services.
How do we understand this in terms of an equity intervention? Let’s go back to Nasir and Hand.
- Access to the domain: Design and data used together is part of what CS people do, bridging students’ concepts and providing an intuitive way of connecting design to the world. When we have data, we can get categories, then schemas and so on. (This matters to CS people, if you’re not one. 🙂 )
- Integral Roles: Students got to see the importance of design, sketching things out, planning, coding, and seeing a segue from non-technical approaches to technical ones. However, one other very important aspect is that the oft-derided “liberal arts” skills may actually be useful or may be a good basis to put coding upon, as long as you understand what programming is and how you can get access to it.
- Making a unique contribution: The students felt that what they were doing was valuable and let them see what they could do.
Take-aways? CS can appeal to so many peopleif we think about how to do it. There are many pathways to help people. We have to think about what we can be doing to help people. Designing for their own community is going to be empowering for people.
Sarah finished on some great questions. How will they handle scaling it up? Apprenticeship is really hard to scale up but we can think about it. Does this make students want to take CS? Will this lead to AP? Can it be inter-leaved with a project course? Could this be integrated into a humanities or social science context? Lots to think about but it’s obvious that there’s been a lot of good work that has gone into this.
What a great session! Really thought-provoking and, while it was a reminder for many of us how far we have left to go, there were probably people present who had heard things like this for the first time.
CSEDU, Day 1, Keynote 2, “Mathematics Teaching: is the future syncretic?” (#csedu14 #csedu #AdelEd)
Posted: April 2, 2014 Filed under: Education | Tags: blogging, community, computer science education, computer supported education, csedu14, design, education, educational problem, heresy, learning, student perspective, students, syncretic, teaching approaches, thinking Leave a commentThis is an extension of the position paper that was presented this morning. I must be honest and say that I have a knee-jerk reaction when I run across titles like this. There’s always the spectre of Rand or Gene Ray in compact phrases of slightly obscure terminology. (You should probably ignore me, I also twitch every time I run across digital hermeneutics and that’s perfectly legitimate.) The speaker is Larissa Fradkin who is trying to improve the quality of mathematics teaching and overall interest in mathematics – which is a good thing and so I should probably be far more generous about “syncretic”. Let’s review the definition of syncretic:
Again, from Wikipedia, Syncretism /ˈsɪŋkrətɪzəm/ is the combining of different, often seemingly contradictory beliefs, while melding practices of various schools of thought. (The speaker specified this to religious and philosophical schools of thought.)
There’s a reference in the talk to gnosticism, which combined oriental mysticism, Judaism and Christianity. Apparently, in this talk we are going to have myths debunked regarding the Maths Wars of Myths, including traditionalist myths and constructivist myths. Then discuss the realities in the classroom.
Two fundamental theories of learning were introduced: traditionalist and constructivist. Apparently, these are drummed into poor schoolteachers and yet we academics are sadly ignorant of these. Urm. You have to be pretty confident to have a go at Piaget: “Piaget studied urchins and then tried to apply it to kids.” I’m really not sure what is being said here but the speaker has tried to tell two jokes which have fallen very flat and, regrettably, is making me think that she doesn’t quite grasp what discovery learning is. Now we are into Guided Teaching and scaffolding with Vygotsky, who apparently, as a language teacher, was slightly better than a teacher of urchins.
The first traditionalist myth is that intelligence = implicit memory (no conscious awareness) + basic pattern recognition. Oh, how nice, the speaker did a lot of IQ tests and went from 70 to 150 in 5 tests. I don’t think many people in the serious educational community places much weight on the assessment of intelligence through these sorts of test – and the objection to standardised testing is coming from the edu research community of exactly those reasons. I commented on this speaker earlier and noted that I felt that she was having an argument that was no longer contemporary. Sadly, my opinion is being reinforced. The next traditionalist myth is that mathematics should be taught using poetry, other mnemonics and coercion.
What? If the speaker is referring to the memorisation of the multiplication tables, we are taking about a definitional basis for further development that occupies a very short time in the learning phase. We are discussing a type of education that is already identified as negative as if the realisation that mindless repetition and extrinsic motivational factors are counter-productive. Yes, coercion is an old method but let’s get to what you’re proposing as an alternative.
Now we move on to the constructivist myths. I’m on the edge of my seat. We have a couple of cartoons which don’t do anything except recycle some old stereotypes. So, the first myth is “Only what students discover for themselves is truly learned.” So the problem here is based on Rebar, 2007, met study. Revelation: Child-centred, cognitively focused and open classroom approaches tend to perform poorly.
Hmm, not our experience.
The second myth is both advanced and debunked by a single paper, that there are only two separate and distinct ways to teach mathematics: conceptual understanding and drills. Revelation: Conceptual advanced are invariably built on the bedrock of technique.
Myth 3: Math concepts are best understood and mastered when presented in context, in that way the underlying math concept will follow automatically. The speaker used to teach with engineering examples but abandoned them because of the problem of having to explain engineering problems, engineering language and then the problem. Ah, another paper from Hung-Hsi Wu, UCB, “The Mathematician and Mathematics Education Reform.” No, I really can’t agree with this as a myth. Situated learning is valid and it works, providing that the context used is authentic and selected carefully.
Ok, I must confess that I have some red flags going up now – while I don’t know the work of Hung-Hsi Wu, depending on a single author, especially one whose revelatory heresy is close to 20 years old, is not the best basis for a complicated argument such as this. Any readers with knowledge in this should jump on to the comments and get us informed!
Looking at all of these myths, I don’t see myths, I see straw men. (A straw man is a deliberately weak argument chosen because it is easy to attack and based on a simplified or weaker version of the problem.)
I’m in agreement with many of the outcomes that Professor Fradkin is advocating. I want teachers to guide but believe that they can do it in the constriction of learning environments that support constructivist approaches. Yes, we should limit jargon. Yes, we should move away from death-by-test. Yes, Socratic dialogue is a great way to go.
However, as always, if someone says “Socratic dialogue is the way to go but I am not doing it now” then I have to ask “Why not?” Anyone who has been to one of my sessions knows that when I talk about collaboration methods and student value generation, you will be collaborating before your seat has had a chance to warm up. It’s the cornerstone of authentic teaching that we use the methods that we advocate or explain why they are not suitable – cognitive apprenticeship requires us to expose our selves as we got through the process we’re trying to teach!
Regrettably, I think my initial reaction of cautious mistrust of the title may have been accurate. (Or I am just hopelessly biassed by an initial reaction although I have been trying to be positive.) I am trying very hard to reinterpret what has been said. But there is a lot of anecdote and dependency upon one or two “visionary debunkers” to support a series of strawmen presented as giant barriers to sensible teaching.
Yes, listening to students and adapting is essential but this does not actually require one to abandon constructivist or traditionalist approaches because we are not talking about the pedagogy here, we’re talking about support systems. (Your take on that may be different.)
There is some evidence presented at the end which is, I’m sorry to say, a little confusing although there has obviously been a great deal of success for an unlisted, uncounted number and unknown level of course – success rates improved from 30 passing to 70% passing and no-one had to be trained for the exam. I would very much like to get some more detail on this as claiming that the syncretic approach is the only way to reach 70% is essential is a big claim. Also, a 70% pass rate is not all that good – I would get called on to the carpet if I did that for a couple of offerings. (And, no, we don’t dumb down the course to improve pass rate – we try to teach better.)
Now we move into on-line techniques. Is the flipped classroom a viable approach? Can technology “humanise” the classroom? (These two statements are not connected, for me, so I’m hoping that this is not an attempt to entail one by the other.) We then moved on to a discussion of Khan, who Professor Fradkin is not a fan of, and while her criticisms of Khan are semi-valid (he’s not a teacher and it shows), her final statement and dismissal of Khan as a cram-preparer is more than a little unfair and very much in keeping with the sweeping statements that we have been assailed by for the past 45 minutes.
I really feel that Professor Fradkin is conflating other mechanisms with blended and flipped learning – flipped learning is all about “me time” to allow students to learn at their own pace (as she notes) but then she notes a “Con” of the Khan method of an absence of “me time”. What if students don’t understand the recorded lectures at all? Well… how about we improve the material? The in-class activities will immediately expose faulty concept delivery and we adapt and try again (as the speaker has already noted). We most certainly don’t need IT for flipped learning (although it’s both “Con” point 3 AND 4 as to why Khan doesn’t work), we just need to have learning occur before we have the face-to-face sessions where we work through the concepts in a more applied manner.
Now we move onto MOOCs. Yes, we’re all cautious about MOOCs. Yes, there are a lot of issues. MOOCs will get rid of teachers? That particular strawman has been set on fire, pushed out to sea, brought back, set on fire again and then shot into orbit. Where they set it on fire again. Next point? Ok, Sebastian Thrun made an overclaim that the future will have only 10 higher ed institutions in 50 years. Yup. Fire that second strawman into orbit. We’ve addressed Professor Thrun before and, after all, he was trying to excite and engage a community over something new and, to his credit, he’s been stepping back from that ever since.
Ah, a Coursera course that came from a “high-quality” US University. It is full of imprecise language, saying How and not Why, with a Monster generator approach. A quick ad hominen attack on the lecturer in the video (He looked like he had been on drugs for 10 years). Apparently, and with no evidence, Professor Fradkin can guarantee that no student picked up any idea of what a function was from this course.
Apparently some Universities are becoming more cautious about MOOCs. Really.
I’m sorry to have editorialised so badly during this session but this has been a very challenging talk to listen to as so much of the underlying material has been, to my understanding, misrepresented at least. A very disappointing talk over all and one that could have been so much better – I agree with a lot of the outcomes but I don’t really think that this is not the way to lead towards it.
Sadly, already someone has asked to translate the speaker’s slides into German so that they can send it to the government! Yes, text books are often bad and a lack of sequencing is a serious problem. Once again I agree with the conclusion but not the argument… Heresy is an important part of our development of thought, and stagnation is death, but I think that we always need to be cautious that we don’t sensationalise and seek strawmen in our desire to find new truths that we have to reach through heresy.
Education and Paying Back (#AdelEd #CSER #DigitalTechnologies #acara #SAEdu)
Posted: March 22, 2014 Filed under: Education, Opinion | Tags: ACARA, advocacy, collaboration, community, cser, cser digital technologies, curriculum, design, digital education, digital technologies, education, educational problem, educational research, Generation Why, Google, higher education, learning, MOOC, Primary school, primary school teacher, principles of design, reflection, resources, school teachers, secondary school, sharing, teaching approaches, thinking, tools 2 CommentsOn Monday, the Computer Science Education Research Group and Google (oh, like you need a link) will release their open on-line course to support F-6 Primary school teachers in teaching the new Digital Technologies curriculum. We are still taking registrations so please go the course website if you want to sign up – or just have a look! (I’ve blogged about this recently as part of Science meets Parliament but you can catch it again here.) The course is open, on-line and free, released under Creative Commons so that the only thing people can’t do is to try and charge for it. We’re very excited and it’s so close to happening, I can taste it!
Here’s that link again – please, sign up!
I’m posting today for a few reasons. If you are a primary school teacher who wants help teaching digital technologies, we’d love to see you sign up and join our community of hundreds of other people who are thinking the same thing. If you know a primary school teacher, or are a principal for a primary school, and think that this would interest people – please pass it on! We are most definitely not trying to teach teachers how to teach (apart from anything else, what presumption!) but we’re hoping that what we provide will make it easier for teachers to feel comfortable, confident and happy with the new DT curriculum requirements which will lead to better experiences all ’round.
My other reason is one that came to me as I was recording my introduction section for the on-line course. In that brief “Oh, what a surprise there’s a camera” segment, I note that I consider the role of my teachers to have been essential in getting me to where I am today. This is what I’d like to do today: explicitly name and thank a few of my teachers and hope that some of what we release on Monday goes towards paying back into the general educational community.
You know who this is for.
My first thanks go to Mrs Shand from my Infant School in England. I was an early reader and, in an open plan classroom, she managed to keep me up with the other material while dealing with the fact that I was a voracious reader who would disappear to read at the drop of a hat. She helped to amplify my passion for reading, instead of trying to control it. Thank you!
In Australia, I ran into three people who were crucial to my development. Adam West was interested in everything so Grade 5 was full of computers (my first computing experience) because he arranged to borrow one and put it into the classroom in 1978, German (I can still speak the German I learnt in that class) and he also allowed us to write with nib and ink pens if we wanted – which was the sneakiest way to get someone’s handwriting and tidiness to improve that I have ever seen. Thank you, Adam! Mrs Lothian, the school librarian, also supported my reading habit and, after a while, all of the interesting books in the library often came through me very early on because I always returned them quickly and in good condition but this is where I was exposed to a whole world of interesting works: Nicholas Fisk, Ursula Le Guin and Susan Cooper not being the least of these. Thank you! Gloria Patullo (I hope I’ve spelt that correctly) was my Grade 7 teacher and she quickly worked out that I was a sneaky bugger on occasion and, without ever getting angry or raising a hand, managed to get me to realise that being clever didn’t mean that you could get away with everything and that being considerate and honest were the most important elements to alloy with smart. Thank you! (I was a pain for many years, dear reader, so this was a long process with much intervention.)
Moving to secondary school, I had a series of good teachers, all of whom tried to take the raw stuff of me and turn it into something that was happier, more useful and able to take that undirected energy in a more positive direction. I have to mention Ken Watson, Glenn Mulvihill, Mrs Batten, Dr Murray Thompson, Peter Thomas, Dr Riceman, Dr Bob Holloway, Milton Haseloff (I still have fossa, -ae, [f], ditch, burned into my brain) and, of course, Geoffrey Bean, headmaster, strong advocate of the thinking approaches of Edward de Bono and firm believer in the importance of the strength one needs to defend those who are less strong. Thank you all for what you have done, because it’s far too much to list here without killing the reader: the support, the encouragement, the guidance, the freedom to try things while still keeping a close eye, the exposure to thinking and, on occasion, the simple act of sitting me down to get me to think about what the heck I was doing and where I was going. The fact that I now work with some of them, in their continuing work in secondary education, is a wonderful thing and a reminder that I cannot have been that terrible. (Let’s just assume that, shall we? Moving on – rapidly…)
Of course, it’s not just the primary and secondary school teachers who helped me but they are the ones I want to concentrate on today, because I believe that the freedom and opportunities we offer at University are wonderful but I realise that they are not yet available to everyone and it is only by valuing, supporting and developing primary and secondary school education and the teachers who work so hard to provide it that we can go further in the University sector. We are lucky enough to be a juncture where dedicated work towards the national curriculum (and ACARA must be mentioned for all the hard work that they have done) has married up with an Industry partner who wants us all to “get” computing (Thank you, Google, and thank you so much, Sally and Alan) at a time when our research group was able to be involved. I’m a small part of a very big group of people who care about what happens in our schools and, if you have children of that age, you’ve picked a great time to send them to school. 🙂
I am delighted to have even a small opportunity to offer something back into a community which has given me so much. I hope that what we have done is useful and I can’t wait for it to start.
Dr Falkner Goes to Canberra Day 1 “How to Tweet Like a Pro” (#smp2014 #AdelED @thesiswhisperer)
Posted: March 17, 2014 Filed under: Education | Tags: Australian National University, bleet, blogging, community, design, education, higher education, Inger Mewburn, irony, Science Meets Parliament, smp2014, thick tweet, thin tweet, thinking, tweet, tweeting, tweets, Twitter Leave a commentThis is going to be somewhat odd as I’m blogging about someone telling me how to tweet and then this blog will get tweeted.
You might want to read that again. I think I’m bleeting.
Seriously, though, I’ve been looking forward to this as social media is not something I’m very good at. I’m certainly very verbose and my exploding stream of text is a familiar sign at the conferences I’m attending but I don’t think I’m very effective. Let’s throw over to Dr Inger Mewburn, Director of Research Training, The Australian National University (@thesiswhisperer) who has a lot more to say about it. (At 13,000 followers, she’s got good credentials, but it took over 40,000 tweets over 4 years to make this happen.)
In 30 minutes, Dr Mewburn is going to cover some Twitter basics (which I won’t share) and some tactics for growing your network (which I will.) (She thinks one of the reasons she’s grown on Twitter is that Twitter is an allied channel in conjunction with her blog and Facebook.)(I seem to like parenthetical comments.)
Twitter can feel like a firehose in the face but you can channel it to read it at your own pace. (I still find it like a firehose, but I really liked the analogy of FaceBook as a street of dinner parties and Twitter as a noisy pub full of people.)
Is Twitter a good way to drive up download and citation of your papers? Downloads appear to go up and citations do, too, (sadly, this is only two data points but it looks interesting). You’re giving stuff away, in effect, but like a DJ rather than Robin Hood.
If you want to focus your blog then pick one main topic and aim 70% of your tweets at that with two other topics that take up the rest. All of these topics should be something that you know about!
Thick and thin tweets (David SIlver): your tweet should send more value than just text.
Seven primary tactics for growing your network (I’m not showing up anywhere so I’m guessing I need to work on this):
- Tell us what’s happening, but use thick tweets – use handles, tags, URLs, link in other people.
- Meet people before you get there (introduce yourself before you show up!)
- Show us something cool (and tell us why). Share cool URLs in a thick way. (“Crafting your links as academic click bait” is the name of my new band. Forward announce and then back announce in the same tweet!
- Please – have an opinion!
- Tweets with pictures get more clicks but they have to be the right pictures. Videos show a boost in tweets about music but not in other topics.
- When someone talks to you, talk back.
- Social media management with a light touch. How do you fit this into your brief time? Use a desktop client (Tweetdeck and Tweetbot) and schedule them for peak hours, morning commute and 8pm, to hit the major periods of reading. Other applications include FlipBoard, Pocket, Zyte (sp?) and Buffer. (Nick note: I must be honest and note that a four application workflow is not what I would call a light touch.)
Lots of great information and really useful – time to start putting it into practice.
SIGCSE Day 2, “Software Engineering: Courses”, Thursday, 1:45-3:00pm, (#SIGCSE2014)
Posted: March 8, 2014 Filed under: Education | Tags: design, education, higher education, Java, Jose Benedetto, learning, open source, principles of design, Robert McCartney, SIGCSE2014, software engineering, students, teaching, teaching approaches Leave a commentRegrettably, despite best efforts, I was a bit late getting back from the lunch and I missed the opening session, so my apologies to Andres Neyem, Jose Benedetto and Andres Chacon, the authors of the first paper. From the discussion I heard, their course sounds interesting so I have to read their paper!
The next paper was “Selecting Open Source Software Projects to Teach Software Engineering” presented by Robert McCartney from University of Connecticut. The overview is why would we do this, the characteristics of the students, the projects and the course, finding good protects, what we found, how well it worked and what the conclusions were.
In terms of motivation, most of their SE course is in project work. The current project approach emphasises generative aspects. However, in most of SE, the effort involves maintenance and evolution. (Industry SE’s regularly tweak and tune, rather than build from the bottom.) The authors wanted to change focus to software maintenance and evolution, have the students working on an existing system, understanding it, adding enhancements, implementing, testing and documenting their changes. But if you’re going to do this, where do you get code from?
There are a lot of open source projects, available on0line, in a variety of domains and languages and at different stages of development. There should* be a project that fits every group. (*should not necessarily valid in this Universe.) The students are not actually being embedded in the open source community, the team is forking the code and not planning to reintegrate it. The students themselves are in 2nd and 3rd year, with courses in OO and DS in Java, some experience with UML diagrams and Eclipse.
For each team of students, they get to pick a project from a set, try to understand the code, propose enhancements, describe and document all o their plans, build their enhancements and present the results back. This happens over about 14 weeks. The language is Java and the code size has to be challenging but not impossible (so about 10K lines). The build time had to fit into a day or two of reasonable effort (which seems a little low to me – NF). Ideally, it should be a team-based project, where multiple developed could work in parallel. An initial look at the open source repositories on these criteria revealed a lot of issues: not many Java programs around 10K but Sourceforge showed promise. Interestingly, there were very few multi-developer projects around 10K lines. Choosing candidate projects located about 1000 candidates, where 200 actually met the initial size criterion. Having selected some, they added more criteria: had to be cool, recent, well documented, modular and have capacity to be built (no missing jar files, which turned out to be a big problem). Final number of projects: 19, size range 5.2-11 k lines.
That’s not a great figure. The takeaway? If you’re going to try and find projects for students, it’s going to take a while and the final yield is about 2%. Woo. The class ended up picking 16 projects and were able to comprehend the code (with staff help). Most of the enhancements, interestingly, involved GUIs. (Thats not so great, in my opinion, I’d always prefer to see functional additions first and shiny second.)
In concluding, Robert said that it’s possible to find OSS projects but it’s a lot of work. A search capability for OSS repositories would be really nice. Oh – now he’s talking about something else. Here it comes!
Small projects are not built and set up to the same standard as larger projects. They are harder to build, less-structured and lower quality documentation, most likely because it’s one person building it and they don’t notice the omissions. Thes second observation is that running more projects is harder for the staff. The lab supervisor ends up getting hammered. The response in later offerings was to offer fewer but larger projects (better design and well documented) and the lab supervisor can get away with learning fewer projects. On the next offering, they increased the project size (40-100K lines), gave the students the build information that was required (it’s frustrating without being amazingly educational). Overall, even with the same projects, teams produced different enhancements but with a lot less stress on the lab instructor.
Rather unfortunately, I had to duck out so I didn’t see Claudia’s final talk! I’ll write it up as a separate post later. (Claudia, you should probably re-present it at home. 🙂 )
Nick Falkner 