Continuing my reading of ‘Inspiring Students: Case Studies in Motivating the Learner’, in this post I look at the case study presented by Stephen Fallows and Kemal Ahmet where architecture and design students undertook ‘experiential practicals’.
Fallows and Ahmet argued that there can be a challenge to motivate students to engage with scientific concepts in disciplines that may require such knowledge but not immediately be identified as science subjects. Describing traditional laboratory based experimental work as requiring significant investment in terms of demonstrators and technicians, but also in terms of time setting up experiments, Fallows and Ahmet suggested that students’ time could be more effectively spent outside the laboratory. Their idea of “experiential practicals” grounds the learning within non-lab contexts, where the task is “to collect scientific data from environments familiar to the student” (p.11). For the students in this case study, they are not handling chemicals or requiring expensive equipment, but the tasks are there to get students familiar with scientific process and data.
Ownership of learning
The ownership of the experimental data is an aspect that Fallows and Ahmet drew attention to. By placing the task, creation of and context of data firmly within a student’s context (their accommodation, for example), there is an immediate sense of ownership, interest and curiosity. We can translate these principles forward to where we are now with learning technologies, particularly where much has been said about the potential for students to ‘bring their own device’ (BYOD) and use digital devices to contribute to teaching sessions. In a lecture environment, a lecturer no longer has to pre-populate a graph with random data to illustrate a point or statistical analysis. Instead, the students can be the source of this data live in the session, via polling tools or adding data to a Google Sheet which then spits out the appropriate graph. There’s not too much of a leap of imagination to take such use of personal digital devices outside of the classroom as the source and means for students to generate data in their own contexts. We’re not limited by numerical data or text-based logs either. Most smartphones have a reasonable still and video camera, many with voice recording apps built in. This provides the opportunity for students to be collecting incredibly rich data-sets for science and non-science disciplines.
Learning through reflection and interpretation
Data collection is not the final step in the learning process Fallows and Ahmet described. A subsequent aspect of their design which engaged students was the analysis and interpretation which occurred through group discussion. This motivated students as they were discussing their own data, comparing to others and through doing so trying to interpret by drawing upon the theory. Whilst these discussions took place in the face-to-face environment, one advantage of modern learning technologies is the ability to capture reflections on the go. Mobile apps for VLE platforms, portfolios and simple text entry can be used to create spaces for students to record their interpretations of data either individually with oversight of their tutor or collaboratively in small groups. To make this work effectively, the interpretation stage must be clearly structured with expectations as to who (student, tutor, peers) will do what (post, interpret, question, feedback) by when. Online activity needs this clearer structure to sustain the motivation and interest of students, in addition to the face-to-face aspects that Fallows and Ahmet detailed in their case study.
The experiential process was outlined by Fallows and Ahmet:
- Concept formally introduced in lecture.
- Instructions for experiential practice given.
- ‘Practical’ carried out (learner gathers information in familiar environments).
- Data processed and results observed.
- Reflection on findings, followed by discussions.
- Concept and theory further reinforced.
When looking at this design and translating to a blended learning approach, there is only one element that requires activity in the physical space: the practical data collection (3). There is certainly scope for theoretical concepts (1) to be delivered via an online lecture, and task instructions (2) to be structured online. Reflection on findings (5a) could be captured via personal devices and results discussed (5b) in an online forum. However, whilst a design could utilise all these approaches, it is worth considering where online approaches may have strengths and where face-to-face approaches may work well. For example, delivery of factual content, collection of data and recording initial thoughts would work well using technology. Value in the final stages of getting students to explain clearly to each other and to question each other can be done more immediately and with a shorter timescale in a face to face environment, in particular so that the lecturer is in a position to reinforce the original concepts and theory (6).
By placing emphasis on interpretation, Fallows and Ahmet indicated their design rewards understanding of underpinning scientific concepts as applied to unique data sets, as opposed to assessing memorisation of principles or facts. Thus, they are able to assess against clear learning objectives, but have designed in creativity and flexibility in the assessed content. The real motivational aspect of this learning design is best summed up in Fallows and Ahmet’s concluding statement: “this method enhances curiosity, ensures student-centred learning and makes learning fun” (p.16). By avoiding unnecessary abstraction and taking advantage of students’ intrigue of the world around them, whether science, social science, arts or humanities subjects, such activities force students to question their own contexts and apply theoretical concepts to them.
Fallows, S. and Ahmet, K. (1999). ‘Experiential Learning Through Practicals’, in Fallows, S. and Ahmet, K. (eds.). Inspiring Students: Case Studies in Motivating the Learner. London: Kogan Page.