Teaching and learning is a process of guided discovery, a shared process where skills and knowledge pass between people. As noted by Northcote and Featherston (2006), teaching and learning are becoming increasingly intertwined, moving away from the traditional uni-directional passage of knowledge. Sometimes learning may begin with a relationship of one-way dependence with the aim of increasing independence at a manageable pace, like gradually removing training wheels when learning to ride a bike. Learning can also happen in a group or network with no specified teacher role, knowledge being created by the sharing of ideas.
This definition is based upon contemporary models and theories of learning design, such as constructivism (e.g. Piaget, 1971; Vygotskiĭ, 1978), experiential learning (Kolb, 2015) and vocational pedagogy (Lucas, Spencer & Claxton, 2012), as well as my own personal preferences as a learner. I discovered during my early experiences as a tertiary student that the widely accepted model of note taking and passage copying was not resulting in my retaining information, nor was it helping me to form my own opinions. Once I realised this, I stopped taking notes about the lecture (especially since most of the information could be found in the readings if I forgot anything) and spent more time listening and thinking, only noting down my own thoughts. Of course, when I have had learning environments available to me other than lectures, I have had a different experience. The learning I personally find most enjoyable and productive is participatory, hands-on where possible and driven by but not focussed on the presence of an expert who helps to prompt discussion.
Because I come from a background of youth adventure training, I tend to view my role a bit like a coach or mentor, helping people to discover knowledge for themselves and building learners’ skills by providing opportunities for practice, feedback and improvement. Like the coach of, say, a football team, the aim is to create “drills” in which to hone the skills that will be useful in a range of unexpected situations, and also to have opportunities to put these skills together into different situations.
To achieve this, I like to include a lot of experiential learning and opportunity for reflection, as well as opportunity for discussion in small or large groups. My own experiences as a learner reinforces this: for example I often relate to my students that when I was first learning to drive, I did not enjoy getting behind the wheel at all, but forcing myself to practice eventually made driving feel second-nature and my anxiety eventually disappeared. For them, this could relate to feeling intimidated by writing tasks, for example. They might feel anxious at first, but the more practice they do, the easier it will feel. Thus I feel that it’s important to curate1 opportunities for learners to put their new skills or knowledge into practice and to learn from early mistakes in order to build confidence. A common way of thinking about this is to compare it with the requirements for learning to fly an aircraft, in which a prospective pilot must log a certain number of flying hours before being allowed to fly solo for the first time. My goal is to incorporate this more into my learning design by introducing “authentic field work” or flying hours as a requirement in Professional Practice type courses. Learners will benefit from the opportunity to work on realistic problems in a workplace-like context (i.e. working in teams to solve IT problems as opposed to the individual following-instructions approach used to learn programming in the first place). The place of the teacher in this comes back to the coach metaphor — to observe the “players” (learners) and identify areas for further improvement and training.
It would be a grave mistake to assume that all students are similar to one another or are similar to myself in terms of their intelligence, motivation, personality and cognitive styles (McKeachie, Pintrich, Lin & Smith , 1986). But in some ways it is a characteristic of human nature to slip back into this view (Ross, Greene & House, 1976), so some effort needs to go into making explicit our perception of the learner so that we can understand where it needs to be corrected.
Intelligence is difficult to measure, and as such there are many different views about what constitutes intelligence (McKeachie, et al., 1986). For the purposes of describing my own perception of the learner, and for the purposes of the kind of teaching I am called upon to do in the Bachelor of Information Technology, I will consider it to be something like a learner’s ability to process new information. The speed at which learners can process information, in my experience, can vary greatly. It can be very challenging teaching a cohort of students where the difference in learning speed between the most and least “intelligent” students is great, and in practice I find that it’s important to check frequently that the speed of learning I am expecting is correct. I endeavour to do this in a way that does not call attention to either the fastest or slowest learners, for example walking around the classroom to view student work and see for myself whether people need more time to complete activities. This is a challenge at times, and I would like to come up with ways to better identify and deal with the different “processing speeds” of different learners. Body language and facial affect display are also important for perceiving intelligence at work.
Motivation and personality can also make a big difference both to individual learners and to a cohort. Where a class has a culture of enthusiastic learning as a result of dominant members of the class displaying motivation and having influential personalities, that class cohort can make a lot more progress in a single semester than one with a culture of indifference. For example, semester one of 2018 was a difficult semester in which I felt at times as though I was struggling to make headway with my first year students. The same course this semester feels easy to teach by comparison, and this is corroborated by my colleagues teaching different courses to the same cohorts. Informal discussion about this phenomenon has identified class culture as a significant influence on individual learner motivation (Ushioda, 2009).
The other aspect that can differ greatly within a single cohort is cognitive style or preferred learning approach (McKeachie, et al., 1986). This makes it important to design learning experiences that can be approached successfully in a range of different ways, which also has the side-effect of making learning more interesting and engaging. For example, I try to design formative assessment that is flexible so as not to restrict learners to a single way to solve a problem. Adding group work to this also means that learners will hopefully be exposed to problem solving approaches they hadn’t considered or encountered yet, thus broadening their tool kit. If an activity is designed with only one successful approach in mind, then these results are missed.
As mentioned in the definition of learning, I do not subscribe to the outdated belief that the learner is a sponge and the teacher is to provide liquid for the learner to endeavour to soak up so that it can be squeezed out later under examination conditions. Here too, the coach metaphor helps to describe my philosophy of the student-teaching relationship: a coach’s job is to identify the need for skill development and provide training in order to prepare the athlete to apply those skills under pressure. Often, and this is also the case in my industry, the application will occur in new or unfamiliar situations. As such, another metaphor might be useful here: training emergency responders. While there are certain skills that must be honed, the training must be flexible enough to result in those skills being applicable in unfamiliar contexts. This links back to my belief that independence and self-reliance, in this case manifesting as the skills of life-long learning and sound decision making, are some of the most important aspects of learning. Information technology never sits still, and as soon as the practitioner learns a new technology someone is already inventing its replacement. In this way, IT will always be full of unfamiliar situations in which to apply the skills we teach.
Another aspect of the student-teaching relationship is that it is not a one-way communication. While the teacher may be the holder of expert knowledge and experience, this does not automatically make them the sole focus of the learning process. The concept of ako (which means both teaching and learning) demonstrates this, in that it expresses learning as a reciprocal process “where the educator is also learning from the student and where educators’ practices are informed by the latest research and are both deliberate and reflective” (Ministry of Education, 2009, p. 20).
An important aspect of the student-teacher relationship is trust, in my context built through a sense of collegiality. Trust is especially important when using teaching and/or assessment methods that learners aren’t used to, such as the concept of more than one correct answer mentioned above. For example, I find it quite difficult to convince my students that I do not employ deductive marking of assessments — they often ask whether they will “lose marks” for incorrect answers or practices. This would not be conducive to curating a safe environment in which to learn from mistakes early on, but learners have often experienced deductive marking before and so it takes time for them to trust that I will allow, or even reward, learning from mistakes.
As an IT teacher, blended learning (Friesen, 2012) is a natural fit for my teaching style and context by using the industry-standard technologies I am teaching as a part of the learning process itself. For example, when I teach GitHub, the lesson can take place within GitHub with face-to-face support at the same time. GitHub is a great way to leave feedback on student work in exactly the same way they would get feedback if they were, for example, developing open source software.
As mentioned earlier, I prefer to stay away from the idea that there is a single right way to do things or a single correct answer, instead preferring to encourage learners to use a robust decision making process and rewarding them for independent thinking. This is part of the goal of creating life long learners, rather than the traditional model of knowledge being passed from teacher to student, remembered by rote and regurgitated for the purpose of an exam. This relates to my personal value of independence and self-reliance. I believe that the ability to make robust decisions will benefit learners well after their ability to predict “correct” answers has become obsolete in the real world. For example, the problems we are called upon to face in the IT industry are often “wicked” problems and do not have single correct solutions (Zack, 1998).
Other teaching methods mentioned already include encouraging discussion, curating safe environments for making and learning from mistakes, designing activities that mimic conditions in the real world of industry and guiding learners to be comfortable with flexible, open-ended assessments. The last of these is also related to the goal of preparing learners for industry, because I believe that the mindset needs to shift from the expectation of being measured by your percentage of correct solutions to an expectation that the individual will need to demonstrate their own professional performance.
In terms of measurable results, the approach of delivering a carefully planned lecture, providing notes for study and assessing with a theory exam covering the content of the lectures for which students cram and rote learn, tends to appear to be a very successful approach to teaching: learners pass the assessment (Michel, Cater & Varela, 2009) and give favourable feedback if the lectures are engaging and the subject interesting to them. However, although immediate results appear to indicate that this is a successful approach to teaching, it does not necessarily follow that learners are able (or willing) to retain what they have learnt for weeks, months or years after they pass the exam (Mayer, 2002).
On the other hand, the approach to teaching outlined in this philosophy document are difficult to measure, sometimes result in mixed feedback from learners (because they have to put in more effort and must genuinely participate actively in the learning process, which some find too challenging) and are often incredibly difficult to implement, especially when faced with an unmotivated cohort who are accustomed to passive learning. But real, genuine learning lasts beyond the final assessment, and this can only be truly achieved when learning is active and teaching is learner-centric. It’s this long-lasting learning that I aim to achieve, regardless of how results appear on paper.
not just create, but curate a safe practice environment where it’s good to fail and learn from it ↩