Wikis help independent learning and transparent assessment in large classes


Author: Dr. Tim Downing, Lecturer in the School of Biotechnology.

I am relatively new to teaching and (like most young lecturers) am employed in a contract-based position. This means I struggle with the seemingly endless whirlpool of teaching new modules without any guarantee that I will teach them in the long-term. Wikis do not solve this, but they make it easier.


Providing individualised assessment to improve learning in large and mixed classes is a major challenge for teaching and learning. A “wiki” is a simple editable database (like Wikipedia) that is familiar to all and can be used for open, independent and collaborative learning. There are many wiki providers that are free for educators and are highly customisable (such as Wikispaces).

1. Wikis permit research-style work and assessment

A wiki can facilitate research-based activity where students are free to choose their topic or question of interest. For example: in one computational biology practical I taught, students assessed the link between a gene and a disease of their choice, which generated a unique topic about which they were personally curious. They investigated this using multiple complementary approaches as instructed over semester-long series of labs, generating their own set of results for interpretation. The students viewed a wiki page containing the instructions and links for the given lab, and added their results for that lab to their own wiki page. The students could refer to a wiki page I provided outlining example answers for a different gene-disease analysis, which they could use as a template for their work. Each student had a single wiki page, which meant that they could refer to and use information from earlier labs, and by the end of term had compiled a substantial amount of work for a summary assignment.

2. Wiki-based discovery could allow better learning and retention

Framing the course across a single concept or question (“does this gene cause this disease?”) means that the assessment has an underlying theme to target the organisation of knowledge, procedures and results in different practicals. This fits into a general for the sciences where practicals can be streamlined as: observed data, comparison with model, decision, feedback and modification [1], similar to an explore-flip-apply layout or the 5E cycle [2]. For practical courses, this can avoid the mere reporting of results using generic procedures with toy datasets, and instead here the students assessed their own data of interest to conduct complementary analyses to address the initial question. Choosing their own gene and disease and not provided ones was used to avoid a research-led rather than research-based manner, which might have caused: “a subset of students each semester adopt the mistaken impression that they’re being ‘used’ by a research laboratory” [3].

A personal research question may improve intrinsic motivation for knowledge organisation, spaced learning and the incorporation of formative feedback. This should assist with increasing active learning (aka engagement: participation, commitment and practice) to tackle their own gene-disease question for which there may not yet be an established answer. A benefit of this is the eventual realisation that information and theory in biology are highly interconnected, non-hierarchical and tend not to have a logical underlying order as often presented in courses.

Why bother with active learning? It reduces the failure rate and advances science students’ conceptual understanding and performance [4] in a dose-dependent manner independent of the specific choice of learning method [5]. Moreover, long-term retention in research has previously been higher in students who took practicals with higher student involvement [6], and either process-driven or discovery-focused authentic research experiences [7].

3. Wikis help with independent learning and managing workloads

Working autonomously provides extensive opportunities for better learning, assuming sufficient student motivation about their chosen question. Allowing students to work when it suits them, which can be tricky for lab-based subjects, means that they can revisit key concepts and observations, and lets them have a better sense of control over their own progress [8]. Though most inevitably are driven by impending deadlines, in this module some students varied their effort such that they started labs in advance of the timetabled period and revisited them periodically, and could work on a report synthesising all the practicals progressively during semester rather than just at the end.

4. Wikis for collaborative learning and feedback

Students in this computational biology module could view one another’s feedback, and could re-submit work after initial feedback: such reflection should assist with a focus on learning rather than on marks. As a result, wikis provide extensive opportunities for group-based tasks, peer instruction and collaborative learning [9], and beyond this permit the dissemination of knowledge as a public service in a open online repository. However, providing more authentic feedback via wikis could be more time-consuming because of the distinctiveness of each student’s strategy and results. Consequently, there is a balance between an ethos of discovery versus feedback efficiency, which can be revised in line with the amount of group-focused tasks, where students assess their partner’s work [10] for instance. For labs like thus one, students could work on multiple genes towards a shared disease, or anonymously review another’s lab report following a rubric [11].

5. Wiki for monitoring of attendance, progress, validity and interest

The wiki interface used here (Wikispaces) recorded the daily number of students logging in, the number of edits made per student, and the number of page views (see Figure). Students viewed content prior to the module start, which helped to address logistical issues prior to the start. Student page edits suggested that they initially completed labs on the same day, before transitioning to a more flexible approach where they also did a portion of the work the day after the lab or before the deadline. This facilitates detailed examination of student engagement, progress and effort over an extended period (semester or beyond).

Editable wikis assist with ensuring the validity of the work, learning citation practises and avoiding plagiarism. The wiki was indexed so that every part could be searched. The edit history of each page was automatically saved, which meant that most mistakes could be reverted easily, and importantly that the incremental and gradual progress expected during a 2-3 hour timeframe for completing a lab in the edit history was a clear contrast to plagiarised work uploaded over 2-3 minutes.

Student-focused semi-structured surveys with open questions are the most effective feedback formats [12], and hence were used to compare student perceptions of the traditional versus the new wiki-based labs. The median student response was more positive across all questions, including specifically the coherence of material, understanding the topic, stimulating interest, and the usefulness of continuous assessment. More students wrote unprompted comments that they specifically liked the new labs (38% wiki versus 15% traditional; none wrote that they disliked the labs).

6. Beyond wikis

Computational biology is a relatively new discipline, but components have become more consistent across courses [13]. This means there are many documented research-based approaches and we are moving towards “An Online Bioinformatics Curriculum” [14] where learning is structured around online resources and independent work. Wikis will play a role in this by providing topic-driven communication platforms with flexible levels of instruction, assessment and feedback [15].

Author: Tim Downing, Lecturer in the School of Biotechnology. I am relatively new to teaching and (like most young lecturers) am employed in a contract-based position. This means I struggle with the seemingly endless whirlpool of teaching new modules without any guarantee that I will teach them in the long-term. Wikis do not solve this, but they make it easier.

Tims Picture

Figure. Daily numbers of student logins (black), edits (white) and views (grey) for the initial labs of a semester-long bioinformatics module (note y-axis log10 scale for the number of views).

Acknowledgements: Thanks to Muireann O’Keeffe (DCU), Cathal Seoighe (NUI Galway) and Sharon Flynn (NUI Galway) for discussions and ideas.



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