Modular degree programmes offer students richness in choice but are also accompanied by concerns regarding cohesion and progression. Here Claire Hughes explores these issues and discusses approaches to defining and mapping the expected progression in our degree programmes.
A coherent learning experience in a modular system
A modular higher education system brings with it increased student choice, opportunities for more immediate and continuing feedback, and is believed to promote learner autonomy and interdisciplinarity (Goldschmid and Goldschmid, 1973; Walker, 1994). Despite its clear benefits this more individualised learning experience is not, however, without its criticism. Some question whether teaching and assessing in discreet packages always provides students with the learning experience needed to develop higher level thinking skills and promote lifelong learning.
Educational theory, such as that detailed in the Science of Successful Learning (Brown et al., 2014), tells us that a balanced, progressive and coherent learning experience which provides students with opportunities for ‘retrieval and interleaving’ is the best way to develop capable graduates. This tells us that the learning within a degree programme will be greater than the sum of that within each its modules if the teaching within each module represents a stepping stone in a well-defined progression. It is easy to see why achieving this could be difficult in a system which offers students the freedom to develop their own bespoke programmes of study.
The expected progression?
Programme-level thinking is clearly essential for guaranteeing that balanced, progressive and coherent learning experience under the modular system. The University Strategy clearly recognises this by putting ‘programme design (and student work) at the heart of our new pedagogy’.
Every programme will have distinctive and clear objectives, and each stage of study will be designed to offer progress towards those programme objectives.
Carefully designed student work will enable students to make progress. Students will understand the work they are expected to do and how that work will contribute to the achievement of the programme objectives.
The ‘careful, collaborative design of a small number of concise, powerful, stretching yet achievable learning outcomes for each programme’ will define what students should be able to do when they graduate and establishes the skills set that our teaching should be aimed towards developing. Our new pedagogy also wants students to understand the expected progression from incoming first year to capable graduate and how, through their individualised, modular programmes of study, they will achieve the programme learning outcomes.
The benefits to students of understanding the expected progression towards programme learning objectives are well-articulated in the new Learning and Teaching Strategy and include an understanding of ‘the coherence of their programme’ and ‘their stage of development within it’, but there are also likely to be advantages for teaching staff. In addition to providing a framework for the design of new modules and the preparation of feedback that informs the learning progression, educational research suggests that so-called curriculum (progression) mapping can be ‘a vehicle for collaboration’ and increases the feeling of collegiality amongst academic staff (Uchiyama and Radin, 2009). The potential benefits are clear but defining and visualising the expected progression in a way that is beneficial for students and teaching staff may seem at first like a daunting task, especially for existing programmes, Much can, however, be learnt from processes that have come before this.
Due to extensive auditing for generic skills in recent years most of us probably now have a good idea of where transferable skills sit within our programmes. Whilst defining the pathway towards degree-specific learning outcomes differs in that it requires an understanding of where discipline/subject-specific skills are taught, the mapping process is essentially the same as that developed for generic skills. There is a wide range of educational research on generic skills auditing that could be of use in this new endeavour. Sumison and Goodfellow (2004), for example, describe an approach to generic skills auditing which is based on the premise that skills development requires training, practice, monitoring and assessment (Gibbs et al., 1994). Their auditing process required module coordinators to complete a survey indicating if generic skills were ‘1. Assumed, 2. Encouraged, 3. Modelled, 4. Explicitly taught, 5. Required or 6. Evaluated’. This provides a depth of information that can be used to check if students are being offered opportunities for utilising newly gained skills or ‘retrieval and interleaving’ (Brown et al., 2014) before they are assessed. A survey of the relevant literature reveals other examples (e.g. Tariq et al., 2004) where similar methods are advocated.
A progression in expectations
Whatever way (and to what extent) we define and communicate the expected progression in our degree programmes it may seem appropriate to accompany this with a progression in our expectations when it comes to assessment. If students are expected to improve and/ or develop new skills as they move through our degree programmes is it unfair to judge them against the same criteria in years 1, 2 and 3 and beyond? Progression maps could be of great use in helping us to define our assessment schedules as they will allow us to identify where the skills included in our programme learning outcomes are taught, practiced, monitored (Gibbs et al., 1994) and ultimately provide guidance on when they can be assessed. This idea has links to the call for the programme-level coordination of assessment detailed in the new Learning and Teaching Strategy.
In the Environment Department here in York we recently introduced programme-wide assessment criteria which map the expected progression in skills from incoming first year to graduating BSc, MSc or MEnv student. We have a different set of assessment criteria for each year of study. Whilst the skills being assessed remain the same, the expectations for some skills increases as students move through the year groups whilst that for some (assumed) skills remains the same.
This means that whilst students may obtain a 1st class degree for a piece of work in first year, the same piece of work would only obtain a 2(i) in second year (and so on) if there is no evidence of progression. In addition to the marking criteria for each year of study we have also developed progression matrices which use colour-coded blocks to show students clearly how they are expected to progress in each skill.
Whilst research has shown that programme-wide marking criteria are not appropriate for all programmes of study (Price and Rust, 1999), mapping the expected progression in subject-specific skills in this way has a clear advantage in that it is linked to assessment which is a big student motivator. Students are perhaps more likely to engage with the progression maps, and hence have a greater understanding of the coherence of their programmes, if they are linked to assessment. For some students simply knowing that there is a progression in expectations when it comes to assessment should be a big motivator to improve as they move through the year groups. In the Environment Department first year students are introduced to the criteria against which they will be assessed throughout their degree during the first few weeks of the autumn term in peer-marking sessions. This means that our students have a map of the expected progression right from the very start of their degree programme.
In summary, the programme-level thinking that sits at the heart of our pedagogy should bring with it great benefits for both students and teachers. In implementing this aspect of our new pedagogy much can be learnt from the sharing of ideas across the university and experiences of generic skills auditing detailed in educational literature.
Brown, P. C., Roediger, H. L. and McDaniel, M. A. (2014) Make it Stick: The Science of Successful Learning. Cambridge MA: Harvard University Press.
Gibbs, G. Rust, C., Jenkins, A. and Jacques, D. (1994) Developing students’ transferable skills. Oxford: The Oxford Centre for Staff Development.
Goldschmid, B. and Goldschmid, M. L (1973) Modular instruction in higher education: a review. High. Edu. 2. p15-32
Price, M. and Rust, C. (1999) The experience of introducing a common criteria assessment grid across an academic department. Qual. High. Edu. 5. p133-144
Sumison, J. and Goodfellow, J. (2004) Identifying generic skills through curriculum mapping: a critical evaluation. High. Edu. Res. Devel. 23. p329-345
Tariq. V. N., Scott, E. M., Cochrane, A. C., Lee, M. and Ryles, L. (2004) Auditing and mapping key skills within university curricula. Qual. Assur. Edu. 12. p70-81
Uchiyama, K. P. and Radin, J. L. (2009) Curriculum mapping in higher education: a vehicle for collaboration. Innov. High. Edu. 33. p271-280
Walker, L. (1994) The new higher education systems, modularity and student capability. In Jenkins, A. and Walker, L. (eds) Developing Student Capability Through Modular Courses. Routledge.
Dr Claire Hughes is a Lecturer in Environmental Chemistry and marine scientist in the Environment Department in York. Claire is a member of the University Learning and Teaching Forum Committee. In terms of teaching she is particularly interested in developing ways to ensure and communicate programme-level coherence and the promotion of student-centred active-learning in science education.