Beautiful decomposition

Now there’s a title that I didn’t expect to write. In this case, I’m referring to how we break group tasks down into individual elements. I’ve already noted that groups like team members who are hard-working, able to contribute and dependable, but we also have the (conflicting) elements from the ideal group where the common goal is more important than individual requirements and this may require people to perform tasks that they are either not comfortable with or ideally suited for.

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Kevin was nervous. The group’s mark depended upon him coming up with a “Knock Knock joke” featuring eyes.

How do we assess this fairly? We can look at what a group produces and we can look at what a group does but, to see the individual contribution, there has to be some allocation of sub-tasks to individuals. There are several (let’s call them interesting) ways that people divide up up tasks that we set. Here are three.

  1. Decomposition into dependent sub-tasks.
  2. Decomposition into isolated sub-tasks (if possible).
  3. Decomposition into different roles that spread across different tasks.

Part of working with a group is knowing whether tasks can be broken down, how that can be done successfully, being able to identify dependencies and then putting the whole thing back together to produce a recognisable task at the end.

What we often do with assignment work is to give students identical assignments and they all solemnly go off and solve the same problem (and we punish them if they don’t do enough of this work by themselves). Obviously, then, a group assignment that can be decomposed to isolated sub tasks that have no dependencies and have no assembly requirement is functionally equivalent to an independent assessment, except with some semantic burden of illusory group work.

If we set assignments that have dependent sub-tasks, we aren’t distributing work pressure fairly as students early on in the process have more time to achieve their goals but potentially at the expense of later students. But if the tasks aren’t dependent then we have the problem that the group doesn’t have to perform as a group, they’re a set of people who happen to have a common deadline. Someone (or some people) may have an assembly role at the end but, for the most part, students could work separately.

The ideal way to keep the group talking and working together is to drive such behaviour through necessity, which would require role separation and involvement in a number of tasks across the lifespan of the activity. Nothing radical about that. It also happens to be the hardest form to assess as we don’t have clear task boundaries to work with. However, we also have provided many opportunities for students to demonstrate their ability and to work together, whether as mentor or mentee, to learn from each other in the process.

For me, the most beautiful construction of a group assessment task is found where groups must work together to solve the problem. Beautiful decomposition is, effectively, not a decomposition process but an identification strategy that can pinpoint key tasks while recognising that they cannot be totally decoupled without subverting the group work approach.

But this introduces grading problems. A fluid approach to task allocation can quickly blur neat allocation lines, especially if someone occupies a role that has less visible outputs than another. Does someone get equal recognition for driving ideas, facilitating, the (often dull) admin work or do you have to be on the production side to be seen as valuable?

I know some of you have just come down heavily on one side or the other reading that last line. That’s why we need to choose assessment carefully here.

If you want effective group work, you need an effective group. They have to trust each other, they have to work to individual strengths, and they must be working towards a common goal which is the goal of the task, not a grading goal.

I’m in deep opinion now but I’ve always wondered how many student groups fall apart because we jam together people who just want a pass with people who would kill a baby deer for a high distinction. How do these people have common ground, common values, or the ability to build a mutual trust relationship?

Why do people who just want to go out and practice have to raise themselves to the standards of a group of students who want to get academic honours? Why should academic honours students have to drop their standards to those of people who are happy to scrape by?

We can evaluate group work but we don’t have to get caught up on grading it. The ability to work in a group is a really useful skill. It’s heavily used in my industry and I support it being used as part of teaching but we are working against most of the things we know about the construction of useful groups by assigning grades for knowledge and skill elements that are strongly linked into the group work competency.

Look at how teams work. Encourage them to work together. Provide escape valves, real tasks, things so complex that it’s a rare person who could do it by themselves. Evaluate people, provide feedback, build those teams.

I keep coming back to the same point. So many students dislike group work, we must be doing something wrong because, later in life, many of them start to enjoy it. Random groups? They’re still there. Tight deadlines? Complex tasks? Insufficient instructions? They’re all still there. What matters to people is being treated fairly, being recognised and respected, and having the freedom to act in a way to make a contribution. Administrative oversight, hierarchical relationships and arbitrary assessment sap the will, undermine morale and impair creativity.

If your group task can be decomposed badly, it most likely will be. If it’s a small enough task that one keen person could do it, one keen person probably will because the others won’t have enough of a task to do and, unless they’re all highly motivated, it won’t be done. If a group of people who don’t know each other also don’t have a reason to talk to each other? They won’t. They might show up in the same place if you can trigger a bribe reaction with marks but they won’t actually work together that well.

The will to work together has to be fostered. It has to be genuine. That’s how good things get done by teams.

Valuable tasks make up for poor motivation. Working with a group helps to practise and develop your time management. Combine this with a feeling of achievement and there’s some powerful intrinsic motivation there.

And that’s the fuel that gets complex tasks done.


Challenge accepted: beautiful groupwork

You knew it was coming. The biggest challenge of any assessment model: how do we handle group-based assessment?

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Come out! We know that you didn’t hand it in on-time!

There’s a joke that says a lot about how students feel when they’re asked to do group work:

When I die I want my group project members to lower me into my grave so they can let me down one more time.

Everyone has horror stories about group work and they tend to fall into these patterns:

  1. Group members X and Y didn’t do enough of the work.
  2. I did all of the work.
  3. We all got the same mark but we didn’t do the same work.
  4. Person X got more than I did and I did more.
  5. Person X never even showed up and they still passed!
  6. We got it all together but Person X handed it in late.
  7. Person W said that he/she would do task T but never did and I ended up having to do it.

Let’s consolidate these. People are concerned about a fair division of work and fair recognition of effort, especially where this falls into an allocation of grades. (Point 6 only matters if there are late penalties or opportunities lost by not submitting in time.)

This is totally reasonable! If someone is getting recognition for doing a task then let’s make sure it’s the right person and that everyone who contributed gets a guernsey. (Australian football reference to being a recognised team member.)

How do we make group work beautiful? First, we have to define the aesthetics of group work: which characteristics define the activity? Then we maximise those as we have done before to find beauty. But in order for the activity to be both good and true, it has to achieve the goals that define and we have to be open about what we are doing. Let’s start, even before the aesthetics, and ask about group work itself.

What is the point of group work? This varies by discipline but, usually, we take a task that is too large or complex for one person to achieve in the time allowed and that mimics (or is) a task you’d expect graduates to perform. This task is then attacked through some sort of decomposition into smaller pieces, many of which are dependant in a strict order, and these are assigned to group members. By doing this, we usually claim to be providing an authentic workplace or task-focused assignment.

The problem that arises, for me, is when we try and work out how we measure the success of such a group activity. Being able to function in a group has a lot of related theory (psychological, behavioural, and sociological, at least) but we often don’t teach that. We take a discipline task that we believe can be decomposed effectively and we then expect students to carve it up. Now the actual group dynamics will feature in the assessment but we often measure the outputs associate with the task to determine how effective group formation and management was. However, the discipline task has a skill and knowledge dimension, while the group activity elements have a competency focus. What’s more problematic is that unsuccessful group work can overshadow task achievement and lead to a discounting of skill and knowledge success, through mechanisms that are associated but not necessarily correlated.

Going back to competency-based assessment, we assess competency by carrying out direct observation, indirect measures and through professional reports and references. Our group members’ reports on us (and our reports on them) function in the latter area and are useful sources of feedback, identifying group and individual perceptions as well as work progress. But are these inherently markable? We spend a lot of time trying to balance peer feedback, minimise bullying, minimise over-claiming, and get a realistic view of the group through such mechanisms but adding marks to a task does not make it more cognitively beneficial. We know that.

For me, the problem with most group work assessment is that we are looking at the output of the task and competency based artefacts associated with the group and jamming them together as if they mean something.

Much as I argue against late penalties changing the grade you received, which formed a temporal market for knowledge, I’m going to argue against trying to assess group work through marking a final product and then dividing those grades based on reported contributions.

We are measuring different things. You cannot just add red to melon and divide it by four to get a number and, yet, we are combining different areas, with different intentions, and dragging it into one grade that is more likely to foster resentment and negative association with the task. I know that people are making this work, at least to an extent, and that a lot of great work is being done to address this but I wonder if we can channel all of the energy spent in making it work into getting more amazing things done?

Just about every student I’ve spoken to hates group work. Let’s talk about how we can fix that.


It’s not just GPAs

If you’re watching the Australian media on higher education, you’ll have seen a lot of discussion regarding the validity of the Australian Tertiary Admission Rank (ATAR) as a measure of a student’s future performance and as an accurate summary of the previous years of education.

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When you are being weighed in the balance, you probably want to know a lot about the scale and the measures.

This article, talking about students being admitted below the cut-offs, contains a lot of discussion on the issue. Not all of the discussion is equally valuable, in my opinion, as the when the question is the validity of the measure, being concerned about ‘standards slipping’ when a lower number is used isn’t that relevant. The interesting parts of the discussion are which mechanisms we should be using and making them transparent so that all students are on a level playing field.

The fact is that students are being admitted to, and passing, courses that have barriers in place which should clearly indicate their chances of success. Yet students are being admitted based on other pathways, using additional measures such as portfolios, and this makes a bit of a mockery on the apparent simplicity of the ATAR system.

My own analysis of student ATAR versus GPA is revelatory: the mapping is a very noisy correlation and, apart from the very highest ATARs, we see people who succeed or fail in a way that does not match their representative ATAR. Yes, there are rough ‘buckets’ but at a granularity of fewer than five buckets, rather than the thousand or so we’re pretending to have.

“Reducing six years of education to a single ranking is simplistic, let’s have a constructive debate about what could replace the ATAR alone as a fairer, more comprehensive and contextual measure of academic potential”.

Iain Martin, from this linked opinion piece.

I couldn’t agree more!


Streamlining for meaning.

In yesterday’s musings on Grade Point Average, GPA, I said:

But [GPA calculation adjustment] have to be a method of avoidance, this can be a useful focusing device. If a student did really well in, say, Software Engineering but struggled with an earlier, unrelated, stream, why can’t we construct a GPA for Software Engineering that clearly states the area of relevance and degree of information? Isn’t that actually what employers and people interested in SE want to know?

This hits at the heart of my concerns over any kind of summary calculation that obscures the process. Who does this benefit? What use it is to anyone? What does it mean? Let’s look at one of the most obvious consumers of student GPAs: the employers and industry.

Feedback from the Australian industry tells us that employers are generally happy with the technical skills that we’re providing but it’s the softer skills (interpersonal skills, leadership, management abilities) that they would like to see more of and know more about. A general GPA doesn’t tell you this but a Software Engineering focused GPA (as I mentioned above) would show you how a student performed in courses where we would expect to see these skills introduced and exercised.

Putting everything into one transcript gives people the power to assemble this themselves, yes, but this requires the assembler to know what everything means. Most employers have neither the time nor inclination to do this for all 39 or so institutions in Australia. But if a University were to say “this is a summary of performance in these graduate attributes”, where the GAs are regularly focused on the softer skills, then we start to make something more meaningful out of an arbitrary number.

But let’s go further. If we can see individual assessments, rather than coarse subject grades, we can start to construct a model of an individual across the different challenges that they have faced and overcome. Portfolios are, of course, a great way to do this but they’re more work to read than single measures and, too often, such a portfolio is weighed against simpler, apparently meaningful measures such as high GPAs and found wanting. Portfolios also struggle if placed into a context of previous failure, even if recent activity clearly demonstrates that a student has moved on from that troubled or difficult time.

I have a deep ethical and philosophical objection to curve grading, as you probably know. The reason is simple: the actions of one student should not negatively affect the outcomes of another. This same objection is my biggest problem with GPA, although in this case the action and outcomes belong to the same student at different points in her or his life. Rather than using performance in one course to determine access to the learning upon which it depends, we make these grades a permanent effect and every grade that comes afterwards is implicitly mediated through this action.

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Sometimes you should be cautious regarding adding curves to address your problems.

Should Past Academic Nick have an inescapable impact on Now and Future Academic Nick’s life? When we look at all of the external influences on success, which make it clear how much totally non-academic things matter, it gets harder and harder to say “Yes, Past Academic Nick is inescapable.” Unfairness is rarely aesthetically pleasing.

An excellent comment on the previous post raised the issue of comparing GPAs in an environment where the higher GPA included some fails but the slightly lower GPA student had always passed. Which was the ‘best’ student from an award perspective? Student A fails three courses at the start of his degree, student B fails three courses at the end. Both pass with the same GPA, time to completion, and number of passes and fails. Is there even a sense of ‘better student’ here? B’s struggles are more immediate and, implicitly, concerns would be raised that these problems could still be active. A has, apparently, moved on in some way. But we’d never know this from simplistic calculations.

If we’re struggling to define ‘best’ and we’re not actually providing something that many people feel is useful, while burdening students with an inescapable past, then the least we can do is to sit down with the people who are affected by this and ask them what they really want.

And then, when they tell us, we do something about changing our systems.


Dances with GPAs

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The trick to dancing with dragons is to never lose your grip on the tail.

If we are going to try and summarise a complicated, long-term process with a single number, and I don’t see such shortcuts going away anytime soon, then it helps to know:

  • Exactly what the number represents.
  • How it can be used.
  • What the processes are that go into its construction.

We have conventions as to what things mean but, when we want to be precise, we have to be careful about our definition and our usage of the final value. As a simple example, one thing that often surprises people who are new to numerical analysis is that there is more than one way of calculating the average value of a group of numbers.

While average in colloquial language would usually mean that we take the sum of all of the numbers and divide them by their count, this is more formally referred to as the arithmetic mean. What we usually want from the average is some indication of what the typical value for this group would be. If you weigh ten bags of wheat and the average weight is 10 kilograms, then that’s what many people would expect the weight to be for future bags, unless there was clear early evidence of high variation (some 500g, some 20 kilograms, for example.)

But the mean is only one way to measure central tendency in a group of numbers. We can also measure the median, the number that separates the highest half of the data from the lowest, or the mode, the value that is the most frequently occurring value in the group.

(This doesn’t even get into the situation where we decide to aggregate the values in a different way.)

If you’ve got ten bags of wheat and nine have 10 kilograms in there, but one has only 5 kilograms, which of these ways of calculating the average is the one you want? The mode is 10kg but the mean is 9.5kg. If you tried to distribute the bags based on the expectation that everyone gets 9.5, you’re going to make nine people very happy and one person unhappy.

Most Grade Point Average calculations are based on a simple arithmetic mean of all available grades, with points allocated from 0 to an upper bound based on the grade performance. As a student adds more courses, these contributions are added to the calculation.

In yesterday’s post, I mused on letting students control which grades go into a GPA calculation and, to explore that, I now have to explain what I mean and why that would change things.

As it stands, because a GPA is an average across all courses, any lower grades will permanently drop the GPA contribution of any higher grades. If a student gets a 7 (A+ or High Distinction) for 71 of her courses and then a single 4 (a Passing grade) for one, her GPA will be 6.875. It can never return to 7. The clear performance band of this student is at the highest level, given that just under 99% of her marks are at the highest level, yet the inclusion of all grades means that a single underperformance, for whatever reason, in three years has cost her standing for those people who care about this figure.

My partner and I discussed some possible approaches to GPA that would be better and, by better, we mean approaches that encourage students to improve, that clearly show what the GPA figure means, and that are much fairer to the student. There are too many external factors contributing to resilience and high performance for me to be 100% comfortable with the questionable representation provided by the GPA.

Before we even think about student control over what is presented, we can easily think of several ways to make a GPA reflect what you have achieved, rather than what you have survived.

  1. We could only count a percentage of the courses for each student. Even having 90% counted means that students who stumble a little once or twice do not have this permanently etched into a dragging grade.
  2. We could allow a future attempt at a course with an improved to replace the previous grade. Before we get too caught up in the possibility of ‘gaming’, remember that students would have to pay for this (even if delayed) in most systems and it will add years to their degree. If a student can reach achievement level X in a course then it’s up to us to make sure that does correspond to the achievement level!
  3. We could only count passes. Given that a student has to assemble sufficient passing grades to be awarded a degree, why then would we include the courses that do not count in a calculation of GPA?
  4. We could use the mode and report the most common mark the student receives.
  5. We could do away with it totally. (Not going to happen any time soon.)
  6. We could pair the GPA with a statistical accompaniment that tells the viewer how indicative it is.

Options 1 and 2 are fairly straight-forward. Option 3 is interesting because it compresses the measurement band to a range of (in my system) 4-7 and this then implicitly recognises that GPA measures for students who graduate are more likely to be in this tighter range: we don’t actually have the degree of separation that we’d assume from a range of 0-7. Option 4 is an interesting way to think about the problem: which grade is the student most likely to achieve, across everything? Option 5 is there for completeness but that’s another post.

Option 6 introduces the idea that we stop GPA being a number and we carefully and accurately contextualise it. A student who receives all high distinctions in first semester still has a number of known hurdles to get over. The GPA of 7 that would be present now is not as clear an indicator of facility with the academic system as a GPA of 7 at the end of a degree, whichever other GPA adjustment systems are in play.

More evidence makes it clearer what is happening. If we can accompany a GPA (or similar measure) with evidence, then we are starting to make the process apparent and we make the number mean something. However, this also allows us to let students control what goes into their calculation, from the grades that they have, as a clear measure of the relevance of that measure can be associated.

But this doesn’t have to be a method of avoidance, this can be a useful focusing device. If a student did really well in, say, Software Engineering but struggled with an earlier, unrelated, stream, why can’t we construct a GPA for Software Engineering that clearly states the area of relevance and degree of information? Isn’t that actually what employers and people interested in SE want to know?

Handing over an academic transcript seems to allow anyone to do this but human cognitive biases are powerful, subtle and pervasive. It is harder for most humans to recognise positive progress in the areas that they are interested in, if there is evidence of less stellar performance elsewhere. I cite my usual non-academic example: Everyone thought Anthony La Paglia’s American accent was too fake until he stopped telling people he was Australian.

If we have to use numbers like this, then let us think carefully about what they mean and, if they don’t mean that much, then let’s either get rid of them or make them meaningful. These should, at a fundamental level, be useful to the students first, us second.


Grades are the fossils of evaluation

Assessments support evaluation, criticism and ranking (Wolff). That’s what it does and, in many cases, that also constitutes a lot of why we do it. But who are we doing it for?

I’ve reflected on the dual nature of evaluation, showing a student her or his level of progress and mastery while also telling us how well the learning environment is working. In my argument to reduce numerical grades to something meaningful, I’ve asked what the actual requirement is for our students, how we measure mastery and how we can build systems to provide this.

But who are the student’s grades actually for?

In terms of ranking, grades allow people who are not the student to place the students in some order. By doing this, we can award awards to students who are in the awarding an award band (repeated word use deliberate). We can restrict our job interviews to students who are summa cum laude or valedictorian or Dean’s Merit Award Winner. Certain groups of students, not all, like to define their progress through comparison so there is a degree of self-ranking but, for the most part, ranking is something that happens to students.

Criticism, in terms of providing constructive, timely feedback to assist the student, is weakly linked to any grading system. Giving someone a Fail grade isn’t a critique as it contains no clear identification of the problems. The clear identification of problems may not constitute a fail. Often these correlate but it’s weak. A student’s grades are not going to provide useful critique to the student by themselves. These grades are to allow us to work out if the student has met our assessment mechanisms to a point where they can count this course as a pre-requisite or can be awarded a degree. (Award!)

Evaluation is, as noted, useful to us and the student but a grade by itself does not contain enough record of process to be useful in evaluating how mastery goals were met and how the learning environment succeeded or failed. Competency, when applied systematically, does have a well-defined meaning. A passing grade does not although there is an implied competency and there is a loose correlation with achievement.

Grades allow us to look at all of a student’s work as if this one impression is a reflection of the student’s involvement, engagement, study, mistakes, triumphs, hopes and dreams. They are additions to a record from which we attempt to reconstruct a living, whole being.

Grades are the fossils of evaluation.

Grades provide a mechanism for us, in a proxy role as academic archaeologist, to classify students into different groups, in an attempt to project colour into grey stone, to try and understand the ecosystem that such a creature would live in, and to identify how successful this species was.

As someone who has been a student several times in my life, I’m aware that I have a fossil record that is not traditional for an academic. I was lucky to be able to place a new imprint in the record, to obscure my history as a much less successful species, and could then build upon it until I became an ACADEMIC TYRANNOSAURUS.

Skull of a Tyrannosaurus Rex at Palais de la Decouverte

LIFE LONG LEARNING, ROAARRRR!

But I’m lucky. I’m privileged. I had a level of schooling and parental influence that provided me with an excellent vocabulary and high social mobility. I live in a safe city. I have a supportive partner. And, more importantly, at a crucial moment in my life, someone who knew me told me about an opportunity that I was able to pursue despite the grades that I had set in stone. A chance came my way that I never would have thought of because I had internalised my grades as my worth.

Let’s look at the fossil record of Nick.

My original GPA fossil, encompassing everything that went wrong and right in my first degree, was 2.9. On a scale of 7, which is how we measure it, that’s well below a pass average. I’m sharing that because I want you to put that fact together with what happened next. Four years later, I started a Masters program that I finished with a GPA of 6.4. A few years after the masters, I decided to go and study wine making. That degree was 6.43. Then I received a PhD, with commendation, that is equivalent to GPA 7. (We don’t actually use GPA in research degrees. Hmmm.) If my grade record alone lobbed onto your desk you would see the desiccated and dead snapshot of how I (failed to) engage with the University system. A lot of that is on me but, amazingly, it appears that much better things were possible. That original grade record stopped me from getting interviews. Stopped me from getting jobs. When I was finally able to demonstrate the skills that I had, which weren’t bad, I was able to get work. Then I had the opportunity to rewrite my historical record.

Yes, this is personal for me. But it’s not about me because I wasn’t trapped by this. I was lucky as well as privileged. I can’t emphasise that enough. The fact that you are reading this is due to luck. That’s not a good enough mechanism.

Too many students don’t have this opportunity. That impression in the wet mud of their school life will harden into a stone straitjacket from which they may never escape. The way we measure and record grades has far too much potential to work against students and the correlation with actual ability is there but it’s not strong and it’s not always reliable.

The student you are about to send out with a GPA of 2.9 may be competent and they are, most definitely, more than that number.

The recording of grades is a high-loss storage record of the student’s learning and pathway to mastery. It allows us to conceal achievement and failure alike in the accumulation of mathematical aggregates that proxy for competence but correlate weakly.

We need assessment systems that work for the student first and everyone else second.


How does competency based assessment work?

From the previous post, I asked how many times a student has to perform a certain task, and to which standard, that we become confident that they can reliably perform the task. In the Vocational Education and Training world this is referred to as competence and this is defined (here, from the Western Australian documentation) as:

In VET, individuals are considered competent when they are able to consistently apply their knowledge and skills to the standard of performance required in the workplace.

How do we know if someone has reached that level of competency?

We know whether an individual is competent after they have completed an assessment that verifies that all aspects of the unit of competency are held and can be applied in an industry context.

The programs involved are made up of units that span the essential knowledge and are assessed through direct observation, indirect measurements (such as examination) and in talking to employers or getting references. (And we have to be careful that we are directly measuring what we think we are!)

A vintage Czech eye chart.

A direct measurement of your eyesight or your ability to memorise Czech eye-charts.

Hang on. Examinations are an indirect measurement? Yes, of course they are here, we’re looking for the ability to apply this and that requires doing rather than talking about what you would do. Your ability to perform the task in direct observation is related to how you can present that knowledge in another frame but it’s not going to be 1:1 because we’re looking at issues of different modes and mediation.

But it’s not enough just to do these tasks as you like, the specification is quite clear in this:

It can be demonstrated consistently over time, and covers a sufficient range of experiences (including those in simulated or institutional environments).

I’m sure that some of you are now howling that many of the things that we teach at University are not just something that you do, there’s a deeper mode of thinking or something innately non-Vocational about what is going on.

And, for some of you, that’s true. Any of you who are asking students to do anything in the bottom range of Bloom’s taxonomy… I’m not convinced. Right now, many assessments of concepts that we like to think of as abstract are so heavily grounded in the necessities of assessment that they become equivalent to competency-based training outcomes.

The goal may be to understand Dijkstra’s algorithm but the task is to write a piece of code that solves the algorithm for certain inputs, under certain conditions. This is, implicitly, a programming competency task and one that must be achieved before you can demonstrate any ability to show your understanding of the algorithm. But the evaluator’s perspective of Dijkstra is mediated through your programming ability, which means that this assessment is a direct measure of programming ability in language X but an indirect measure of Dijkstra. Your ability to apply Dijkstra’s algorithm would, in a competency-based frame, be located in a variety of work-related activities that could verify your ability to perform the task reliably.

All of my statistical arguments on certainty from the last post come back to a simple concept: do I have the confidence that the student can reliably perform the task under evaluation? But we add to this the following: Am I carrying out enough direct observation of the task in question to be able to make a reliable claim on this as an evaluator?

There is obvious tension, at modern Universities, between what we see as educational and what we see as vocational. Given that some of what we do falls into “workplace skills” in a real sense, although we may wish to be snooty about the workplace, why are we not using the established approaches that allow us to actually say “This student can function as an X when they leave here?”

If we want to say that we are concerned with a more abstract education, perhaps we should be teaching, assessing and talking about our students very, very differently. Especially to employers.


Too big for a term? Why terms?

I’ve reached the conclusion that a lot of courses have an unrealistically high number of evaluations. We have too many and we pretend that we are going to achieve outcomes for which we have no supporting evidence. Worse, in many cases, we are painfully aware that we cause last-minute lemming-like effects that do anything other than encourage learning. But why do we have so many? Because we’re trying to fit them into the term or semester size that we have: the administrative limit.

One the big challenges for authenticity in Computer Science is the nature of the software project. While individual programs can be small and easy to write, a lot of contemporary programming projects are:

  1. Large and composed of many small programs.
  2. Complex to a scale that may exceed one person’s ability to visualise.
  3. Long-lived.
  4. Multi-owner.
  5. Built on platforms that provide core services; the programmers do not have the luxury to write all of the code in the system.

Many final year courses in Software Engineering have a large project courses, where students are forced to work with a (usually randomly assigned) group to produce a ‘large’ piece of software. In reality, this piece of software is very well-defined and can be constructed in the time available: it has been deliberately selected to be so.

Is a two month software task in a group of six people indicative of real software?

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June 16: Remember to curse teammate for late delivery on June 15.

Yes and no. It does give a student experience in group management, except that they still have the safe framework of lecturers over the top. It’s more challenging than a lot of what we do because it is a larger artefact over a longer time.

But it’s not that realistic. Industry software projects live over years, with tens to hundreds of programmers ‘contributing’ updates and fixes… reversing changes… writing documentation… correcting documentation. This isn’t to say that the role of a university is to teach industry skills but these skill sets are very handy for helping programmers to take their code and make it work, so it’s good to encourage them.

I believe finally, that education must be conceived as a continuing reconstruction of experience; that the process and the goal of education are one and the same thing.

from John Dewey, “My Pedagogic Creed”,  School Journal vol. 54 (January 1897)

I love the term ‘continuing reconstruction of experience’ as it drives authenticity as one of the aesthetic characteristics of good education.

Authentic, appropriate and effective learning and evaluation activities may not fit comfortably into a term. We already accept this for activities such as medical internship, where students must undertake 47 weeks of work to attain full registration. But we are, for many degrees, trapped by the convention of a semester of so many weeks, which is then connected with other semesters to make a degree that is somewhere between three to five years long.

The semester is an artefact of the artificial decomposition of the year, previously related to season in many places but now taking on a life of its own as an administrative mechanism. Jamming things into this space is not going to lead to an authentic experience and we can now reject this on aesthetic grounds. It might fit but it’s beautiful or true.

But wait! We can’t do that! We have to fit everything into neat degree packages or our students won’t complete on time!

Really?

Let’s now look at the ‘so many years degree’. This is a fascinating read and I’ll summarise the reported results for degree programs in the US, which don’t include private colleges and universities:

  • Fewer than 10% of reporting institutions graduated a majority of students on time.
  • Only 19% of students at public universities graduate on-time.
  • Only 36% of state flagship universities graduate on-time
  • 5% of community college students complete an associate degree on-time.

The report has a simple name for this: the four-year myth. Students are taking longer to do their degrees for a number of reasons but among them are poorly designed, delivered, administered or assessed learning experiences. And jamming things into semester blocks doesn’t seem to be magically translating into on-time completions (unsurprisingly).

It appears that the way we break up software into little pieces is artificial and we’re also often trying to carry out too many little assessments. It looks like a good model is to stretch our timeline out over more than one course to produce an experience that is genuinely engaging, more authentic and more supportive of long term collaboration. That way, our capstone course could be a natural end-point to a three year process… or however long it takes to get there.

Finally, in the middle of all of this, we need to think very carefully about why we keep using the semester or the term as a container. Why are degrees still three to four years long when everything else in the world has changed so much in the last twenty years?


Is an IDE an E3? Maybe an E2?

Earlier, I split the evaluation resources of a course into:

  • E1 (the lecturer and course designer),
  • E2 (human work that can be based on rubrics, including peer assessment and casual markers),
  • E3 (complicated automated evaluation mechanisms)
  • E4 (simple automated evaluation mechanisms, often for acceptance testing)

E1 and E2 everyone tends to understand, because the culture of Prof+TA is widespread, as is the concept of peer assessment. In a Computing Course, we can define E3 as complex marking scripts that perform amazing actions in response to input (or even carry out formal analysis if we’re being really keen), with E4 as simple file checks, program compilation and dumb scripts that jam in a set of data and see what comes out.

But let’s get back to my first year, first exposure, programming class. What I want is hands-on, concrete, active participation and constructive activity and lots of it. To support that, I want the best and most immediate feedback I can provide. Now I can try to fill a room with tutors, or do a lot of peer work, but there will come times when I want to provide some sort of automated feedback.

Given how inexperienced these students are, it could be a quite a lot to expect them to get their code together and then submit it to a separate evaluation system, then interpret the results. (Remember I noted earlier on how code tracing correlates with code ability.)

Thus, the best way to get that automated feedback is probably working with the student in place. And that brings us to the Integrated Development Environment (IDE). An IDE is an application that provides facilities to computer programmers and helps them to develop software. They can be very complicated and rich (Eclipse), simple (Processing) or aimed at pedagogical support (Scratch, BlueJ, Greenfoot et al) but they are usually made up of a place in which you can assemble code (typing or dragging) and a set of buttons or tools to make things happen. These are usually quite abstract for early programmers, built on notional machines rather than requiring a detailed knowledge of hardware.

Screen Shot 2016-01-31 at 4.12.01 PM

The Processing IDE. Type in one box. Hit play. Rectangle appears.

Even simple IDEs will tell you things that provide immediate feedback. We know how these environments can have positive reception, with some demonstrated benefits, although I recommend reading Sorva et al’s “A Review of Generic Program Visualization Systems for Introductory Programming Education” to see the open research questions. In particular, people employing IDEs in teaching often worry about the time to teach the environment (as well as the language), software visualisations, concern about time on task, lack of integration and the often short lifespan of many of the simpler IDEs that are focused on pedagogical outcomes. Even for well-established systems such as BlueJ, there’s always concern over whether the investment of time in learning it is going to pay off.

In academia, time is our currency.

But let me make an aesthetic argument for IDEs, based on the feedback that I’ve already put into my beautiful model. We want to maximise feedback in a useful way for early programmers. Early programmers are still learning the language, still learning how to spell words, how to punctuate, and are building up to a grammatical understanding. An IDE can provide immediate feedback as to what the computer ‘thinks’ is going on with the program and this can help the junior programmer make immediate changes. (Some IDEs have graphical representations for object systems but we won’t discuss these any further here as the time to introduce objects is a subject of debate.)

Now there’s a lot of discussion over the readability of computer error messages but let me show you an example. What’s gone wrong in this program?

 

Screen Shot 2016-01-31 at 4.20.22 PM

See where that little red line is, just on the end of the first line? Down the bottom there’s a message that says “missing a semicolon”. In the Processing language, almost all lines end with a “;” so that section of code should read:

size(200,200);
rect(0,10,100,100);

Did you get that? That missing semicolon problem has been an issue for years because many systems report the semicolon missing on the next line, due to the way that compilers work. Here, Processing is clearly saying: Oi! Put a semi-colon on the red squiggle.

I’m an old programmer, who currently programs in Java, C++ and Processing, so typing “;” at the end of a line is second nature to me. But it’s an easy mistake for a new programmer to make because, between all of the ( and the ) and the , and the numbers and the size and the rect… what do I do with the “;”?

The Processing IDE is functioning in at least an E4 mode: simple acceptance testing that won’t let anything happen until you fix that particular problem. It’s even giving you feedback as to what’s wrong. Now this isn’t to say that it’s great but it’s certainly better than a student sitting there with her hand up for 20 minutes waiting for a tutor to have the time to come over and say “Oh, you’re missing a semicolon.”

We don’t want shotgun coding, where random fixes and bashed-in attempts are made desperately to solve a problem. We want students to get used to getting feedback on how they’re going and using this to improve what they do.

Because of Processing’s highly visual mode, I think it’s closer to E3 (complex scripting) in many ways because it can tell you if it doesn’t understand what you’re trying to do at all. Beyond just not doing something, it can clearly tell you what’s wrong.

But what if it works and then the student puts something up on the screen, a graphic of some sort and it’s not quite right? Then the student has started to become their own E2, evaluating what has happened in response to the code and using human insight to address the shortfall and make changes. Not as an expert but, with support and encouragement, a developing expertise.

Feedback is good. Immediacy is good. Student involvement is good. Code tracing is linked to coding ability. A well-designed IDE can be simple and engage the student to an extent that is potentially as high as E2, although it won’t be as rich, without using any other human evaluation resources. Even if there is no other benefit, the aesthetic argument is giving us a very strong nudge to adopt an appropriate IDE.

Maybe it’s time to hang up the command line and live in a world where IDEs can help us to get things done faster, support our students better and make our formal human evaluation resources go further.

What do you think?


Small evaluation, big impact.

One of the problems with any model that builds in more feedback is that we incur both the time required to produce the feedback and we also have an implicit requirement to allow students enough time to assimilate and make use of it. This second requirement is still there even if we don’t have subsequent attempts at work, as we want to build upon existing knowledge. The requirement for good feedback makes no sense without a requirement that it be useful.

But let me reiterate that pretty much all evaluation and feedback can be very valuable, no matter how small or quick, if we know what we are trying to achieve. (I’ll get to more complicated systems in later posts.)

Novice programmers often struggle with programming and this early stage of development is often going to influence if they start off thinking that they can program or not. Given that automated evaluation only really provides useful feedback once the student has got something working, novice programming classes are an ideal place to put human markers. If we can make students think “Yes, I can do this” early on, this is the emotion that they will remember. We need to get to big problems quickly, turn them into manageable issues that can be overcome, and then let motivation and curiosity take the rest.

C64_startup_animiert

That first computer experience can stay with you your whole life. (Mine was actually punch cards but they don’t blink.)

There’s an excellent summary paper on computer programming visualisation systems aimed at novice programmers, which discusses some of the key problems novices face on their path to mastery:

  1. Novices can see some concepts as code rather than the components of a dynamic process. For example, they might see objects as simply a way of containing things rather than modelling objects and their behaviours. These static perceptions prevent the students from understanding that they are designing behaviours, not just writing magic formulas.
  2. There can be significant difficulties in understanding the computer, seeing the notional machine that is the abstraction, forming a basis upon which knowledge of one language or platform could be used elsewhere.
  3. Misunderstanding fundamental concepts is common and such misconceptions can easily cause weak understanding, leaving the students in the liminal state, unable to assimilate a threshold concept and move on.
  4. Students struggle to trace programs and work out what state the program should be in. In my own community, Raymond Lister, Donna Teague, Simon, and others have clearly shown that many students struggle with the tracing of even simple programs.

If we have put human markers (E1 or E2) into a programming class and identified that these are the problems we’re looking for, we can provide immediate targeted evaluation that is also immediate constructive feedback. On the day, in response to actual issues, authentic demonstration of a solution process that students can model. This is the tightest feedback and reward loop we can offer. How does this work?

  • Program doesn’t work because of one of the key problem areas.
  • Human evaluator intervenes with student and addresses the issue, encouraging discovery inside the problem area.
  • Student tries to identify problem and explains it to evaluator in context, modelling evaluator and based on existing knowledge.
  • Evaluator provides more guidance and feedback.
  • Student continues to work on problem.
  • We hope that the student will come across the solution (or think towards it) but we may have to restart this loop.

Note that we’re not necessarily giving the solution here but we can consider leading towards this if the student is getting visibly frustrated. I’d suggest never telling a student what to type as it doesn’t address any of the problems, it just makes the student dependent upon being told the answer. Not desirable. (There’s an argument here for rich development environments that I’ll expand on later.)

Evaluation like this is formative, immediate and rich. We can even streamline it with guidelines to help the evaluators although much of this will amount to supporting students as they learn to read their own code and understand the key concepts. We should develop students simple to complex, concrete to abstract, so some problems with abstraction are to be expected, especially if we are playing near any threshold concepts.

But this is where learning designers have to be ready to say “this may cause trouble” and properly brief the evaluators who will be on the ground. If we want our evaluators to work efficiently and effectively, we have to brief them on what to expect, what to do, and how to follow up.

If you’ve missed it so far, one of our big responsibilities is training our evaluation team. It’s only by doing this that we can make sure that our evaluators aren’t getting bogged down in side issues or spending too much time with one student and doing the work for them. This training should include active scenario-based training to allow the evaluators to practise with the oversight of the educators and designers.

We have finite resources. If we want to support a room full of novices, we have to prepare for the possibility of all of them having problems at once and the only way to support that at scale is to have an excellent design and train for it.