CHAPTER 4

How Do Students Develop Mastery?

Principle: To develop mastery, students must acquire component skills, practice integrating them, and know when to apply what they have learned.

Key points of this chapter are:

• Tasks that seem simple and straightforward to instructors often involve a complex combination of skills: the problem of the Expert Blind Spot
  Reflecting on the four stages in the development of mastery was a valuable opportunity to me. I had already seen the four stages in a recent seminar and I was curious to learn more.
  The fact that students and instructors are at the two extremities of the range (students are unconscious incompetent, whereas instructor are unconscious competent) causes these latter to become blind to the actual learning needs of novice students. The time distance from the period of our life in which we where students and we had to struggle with the difficulties of developing mastery, makes us susceptible to expert blind spots, and to lose the ability of following the mental patterns of our students. We also often “forget” the appropriate language to explain things easily: despite I try to explain the meaning and usage of each single jargon term I introduce in courses, sometimes I realise I use words students don’t understand correcly because their meaning depends on the context. For example, I remember once I was talking about “classes of objects” and some students thought I was talking about Python classes, whereas I meant “categories of objects”. So, now, in Python courses, I pay attention to not use the word “class” when I mean “category”. In order to (try to) smooth the difficulties emerging from the expert-novice distance, I create as many peer instruction opportunities as possible and ask students to make recaps aloud. Indeed, I find these practices helpful to both the students who teach/recap/present and to students who receive teaching/recapping/presentation. In the feedback questionnaires students are asked to fill in at the end of courses, I always insert the question: “what did you like most in the course?”. More than 50% of answers concern interactive activities (work in groups/pairs, peer instruction, presenting, recapping, discussions, brainstorming). This may be an indication that learning from peers is an important part of the whole story.
  The fact that instructor mastery - instead of facilitating - may impair students’ learning may seem counter-intuitive. But we all have experienced it when we were students. I remember a Python instructor - many years ago - starting a course by talking two hours about regular expressions and connecting them to the usage of the Linux command grep and to functional motif matching in protein sequences. The audience was mostly made up of biologists who were barely capable of using programs like Microsoft Office.
  This was an example of a teacher who had no idea about the kind of audience he was teaching to and no awareness about pedagogical principles.
  In order to avoid the expert blind spot we need to be aware of the problem, to develop as much empathy as possible, to know as much as possible about our students’ background (and prior knowledge, see chapter 1 of the book) and work hard in lesson/course preparation.
  In the classroom, I make a big effort to keep myself constantly aware of the differences in the way of thinking (and the knowledge organisation) about a topic between myself and my students. I also try to think how they might think and what their mental patterns could be. I try to figure out how a world without certain solutions, e.g., Python lists or tuples, might look like, or what kind of objects do take shape in students’ mind when I refer to, e.g., “containers”. When I’m teaching (especially to novices), I try to focus on a single concept at a time, then I try to identify all the fundamentals needed to understand that concept and finally I ensure students are familiar with them. If they are not, I explain again what is missing or weak. I connect objects only after that. For example, when I teach Linux commands, I avoid describing a large number of commands. I rather explain what lays behind commands (input/output, the shell, the PATH environment variables, scripts, etc.) because I believe that once they consolidate the fundamentals about commands and understand it is always the same story ( -option ), they can do nearly everything they need with the help of a Linux cheat sheet.
  Having said that, I have to recognise I should think more and more deeply about all these aspects when I prepare new lessons or courses.
  This is a more general comment about my work as a teacher: in course/lesson design and teaching materials preparation I should be much more driven by learning principles than I currently am.
  Currently, in designing a course/lesson, I first identify the target audience and training needs. Then I make a syllabus and then I develop a lesson and related practicals/exercises for each item of the syllabus. This means that I'm mostly focused on the content rather than on pedagogical aspects. Despite introducing a more pedagogical approach in preparing lessons and materials may be hugely demanding (especially in terms of time), I think I really should make an effort in this direction.

• Experts and novices differ not only in the amount of knowledge but also in the way they organise, access, and apply their knowledge.

• How can we help students ACQUIRE component skills. “Instructors must be able to “unpack” or decompose complex tasks” and “identify component skills”. This can be very challenging, especially if the component skills involve “purely cognitive processes, such as recognising, planning, formulating, etc. that are not directly visible”. Some strategies suggested in this section look particularly helpful.
  The strategy to determine whether we have identified all the component skills relevant for a particular task seems quite easy to try. The indication is: “keep asking yourself ‘What would students have to know - or know how to do - in order to achieve what I am asking of them?”. The authors suggest we keep asking this question until we have identified all the key component skills. But who/what can ensure we have really identified all the component skills?
  
  Another suggested strategy is: “Enlist a teaching assistant or graduate student to help with task decomposition”. This is undoubtedly helpful. I wonder whether it would make sense to also develop “task decomposition exercises” and make them together with our students.
  
  I found more than interesting the suggestions provided in the following proposed strategy: “Focus students’ attention on key aspects of the task”. Despite clearly communicating our goals and priorities by telling students where to put their energies - and also where not to - may seem self-evident, it is something I never did consciously. I found even more compelling the suggestion of using rubrics that spell out our performance criteria for particular asignments to help students focus their cognitive resources where they best serve our learning objectives.
  I read Appendix C (“What are rubrics and how can we use them?”) and realised rubrics may be a very powerful teaching technique, especially if given to students with the assignment description, so that students can monitor and assess their progress as they work toward clearly indicated goals.
  Before reading this, I didn’t think rubrics could be used for something else than grading or ranking. I’m very curious to know if/how they could work in students’ self-assessment.

Learning more about rubrics made me think about the possibility of developing a rubric for teachers’ self-assessment. This is unrelated to the topic of this chapter, but since I would like to think more about this, I took some notes at the end of this blog.

• How can we help students INTEGRATE skills?
  Multi-tasking has been observed to reduce people performance. Experts can combine multiple tasks relatively easily (because of fluency and automaticity in each of the component skills), still I think their performance is not as good as when they are focussed on a single task. In our daily life, we are constantly forced to combine tasks. I personally find it exhausting and frustrating because I’m constantly left with the impression I didn’t do things as I should have done. Novices suffer much more from performing complex tasks than experts and, when the cognitive load is too intensive, learning is impaired. Even without being aware of this pedagogical principle, during my career as a teacher, I went from assigning very inclusive exercises (with the idea of providing students with a global picture of a problem) to very small and specific exercises. This was the outcome of observing students’ difficulties in performing complex exercises. I also increased the proportion of time allocated to do practicals versus theory. Now I do my best to avoid lecturing more than 15 minutes out of 60 minutes classes. Despite I allocate a lot of time for practicing, one of the most frequent complaints students write in feedback questionnaires is “too little time to work out exercises”. I realise now this must be related to an exceeding cognitive load and I’ve to prepare my classes keeping my eyes open on this issue. Here, I’ve become aware of two more things, which will be very helpful in preparing and delivering my future classes. One is the worked-example effect and another one is the distinction between extraneous and germane load. As for the former, I’ve always being convinced that pushing students to understand a concept by themselves or achieve a goal with no or very little help is a way to imprint the concept or make clear once forever the procedure to achieve a goal. I had no idea this could be too demanding in terms of cognitive load. Normally, I show (e.g. using live coding) how to solve a problem, but usually after having let them struggle for a while to find their own solution. I think I should revise some of the sessions of my Python course in order to show students potential solutions before assigning them challenges I want them to solve by themselves.
  Being aware of extraneous and germane load will definitely help me prepare more effective teaching sessions.
  As previously mentioned, I don’t teach Linux commands. I rather teach the theory behind and then I provide students with a cheat sheet to execute a tutorial. I also explicitly tell them that they are not required to learn commands during the Linux session, rather they are expected to make use of the cheat sheet. I have come up with this approach because it works and because remembering commands becomes natural as soon as studens use them. So, I think it is a waste of time to show a list of commands and use the little time available to describe the action of each of them.
  Being aware of extraneous and germane load, will help me to systematically reflect more on what is the main goal of each part of a lesson/course and identify which skills students need to learn and which may be distracting from the learning goal.
  I mean to combine in future teaching the follwoing strategies suggested in this section: Give students practice to increase fluency and Temporarily constrain the scope of the task. One the one hand, I mean to reduce the size or complexity of many tasks and, on the other, allocate more time (in classroom and/or at home if the type of course allows for it) to work out exercises specifically designed to increase students’ speed and efficiency. I also want to become more explicit about the level of fluency I expect students to achieve. Once they have reached a good level of fluency in a number of essential tasks, I will add additional elements connecting them.

I forsee a lot of work in future course preparation and delivery…

• How can we help students KNOW WHEN TO APPLY skills
  Due to time issues, far transfer may be a too ambitious objective to achieve in short training courses. I would be more than happy if I were able to help students transfer skills, knowledge, or practices they learn in my courses to their own field of research (very near transfer). To this end, I already make use of some strategies described in this section. For example, I show how to parse files having a specific format, e.g. tab-separated. Then I tell students to parse the typical file they have to deal with in every day data analysis or files with a different format.
  I also ask questions and propose discussions aimed at stimulating students to identify contexts in which a given skill or knowledge can be applied and - given a context - I ask them to identify skills that are appropriate for that context. For example, I describe a realistic situation (“You need to read several fasta files from a directory and only move to a different directory files containing sequences from Homo sapiens”) and then I ask students to make a list of all the skills they need to perform this task. Then I describe a different realisitc situation (for which I know similar skills are needed) and ask students to repeat the exercise. Then we compare.

What makes a good teacher? Does it exist (and, if not, would it make sense to develop) a rubric to help teachers self-evaluate?
It is absolutely possible that researchers have already produced something similar but, due to my ignorance, I don’t know it. In ELIXIR’s Train the Trainer courses, we ask participants to write down and discuss in groups qualities that make a teacher a good teacher. The purpose of this exercise is to encourage TtT trainees to reflect on such characteristics and try to find out if they have them.
However, it is very difficult for a teacher to determine in a clear and if possible objective manner whether she is a good teacher. For example, I can say I feel passion for teaching, but it is much more difficult to determine, e.g., how much I’m empathic or aware of pedagogical principles while teaching. It would be very helpful to have a scoring tool that could be used in self-assessment.
I wonder whether it would make sense to have a rubric providing clear descriptions of different levels of quality associated with each characteristic.

Potential characteristics to be assessed (not in order of relevance):

• Empathy
• Knowledge of and enthusiasm for the discipline/subject
• Passion/motivation for teaching
• Awareness of pedagogical principles (how learning works)
• Ability to apply pedagogical principles in teaching
• Ability to listen
• Be/become a good performer
• Fairness

How much difficult would be associating quantitative scores to these qualitative features? With reference to Exhibit C.1., would it be possible to develop appropriate descriptions defining Exemplary, Competent, Developing, etc. teachers?