Methods for Innovation
Methods for Innovation
Changes to theory delivery
As mentioned in the previous section, lectures deliver information to students, but only develop the lower level cognitive skills without additional support. Students must be given concrete experiences to reflect on in order to truly learn( Kolb, 1984). The lectures were changed to combine the delivery of information with regular example questions. For topics where example questions are not applicable, other methods are used to give students concrete experiences. For example, the lecture on internal hardware of a computer combines lecture slides with a live dissection of a computer, where students could handle individual components. Most importantly, these lectures were backed up with weekly problem classes devoted to the topic of that week’ s lecture. Work for these classes is released immediately after the lecture for students to attempt before class. Students are now able to have concrete experiences in the lectures, reflect on these between the lecture and problem class, and to then attempt active experimentation when presented with the problems.
These additional classes were supplemented with learning materials to be used outside of taught sessions, catering for students with different learning methods. For example, an interactive binary calculator was written in Excel, giving students visual solutions to conversions between base numbers, as well as fixed and floating point binary numbers. For those students with a less visual approach, the underlying formulae could be accessed and deconstructed. Since the examination covered two semesters worth of work, the students were also given an‘ Exam Survival Guide’ at the end of the second semester. This 39-page document covered every examinable topic, required methods and exam technique.
Programming Teaching and Assessment
One of the biggest changes made to the programming side of the module was the removal of the assembly language assignment, due to the intended learning outcomes being covered elsewhere, the relative irrelevance of low-level languages and the amount of assessment. However, assembly language was listed amongst the indicative content in the module outline, and so was not removed from the module entirely. It was instead incorporated into the theory side of the module as a part of the finite state machines topic.
The programming side of the module was completely restructured. Processing was retained, but the first semester is now devoted to learning different transferable techniques for coding in Processing. Each of these techniques is then assessed in the final portfolio. The semester culminates in a lecture on program planning, with the program planning assignment completed over the Christmas vacation. This feeds into the second semester, where the lab sessions are used to develop a game based on the plan. This is an example of the kind of problem-based learning that has previously been used successfully to teach programming( O’ Kelly and Gibson, 2006).
There are several advantages to this. Firstly, having the program plans submitted prior to the second semester, rather than as part of the final portfolio, means that the students think ahead about breaking down a problem into steps, rather than completing it based on the final program design. This is more in keeping with intended learning outcomes 3, 4 and 6. Secondly, the portfolio assesses how well the students have met learning outcomes 2, 3, 4, 5, 6 and 7, meaning that the programming side of the module is constructively aligned( Biggs, 1996). Finally, by giving the students the opportunity to direct their own learning in the second semester, the students gain independent study skills that will benefit them on a Computer Science degree.
The changes to the programming labs drew on a range of literature. They now use a scaffolding approach, where students are given support from staff when beginning to learn new concepts before the level of support is gradually reduced over time( Wood, Bruner and Ross, 1976), and a spiral curriculum, which begins with a relatively simple concept that is then built upon until mastery of the subject is achieved( Bruner, 1996). Tan, Ting and Ling( 2009) found that programming students respond poorly to lecturing and prefer to work from interactive examples, while Jenkins( 2001) indicated that teaching programming is not about transmitting information but motivating students to
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