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Diagnostic Tool and Content Management System

Why use diagnostics?

“Students must be effective self-assessors; to be anything less is to be dangerously ill-prepared to cope with change”

(Boud 2000, p. 160).

As part of the development of both sound academic practice and lifelong learning skills, the ability to make self-evaluative assessment of competencies, attributes and learning preferences/needs are vital. Therefore, students need to have a clear understanding of what these are, how to acquire and/or develop them, and the confidence to apply them. To do this, students need opportunities, beyond formal assessment and feedback, to reflect on the competencies they require and to recognise their attributes, strengths and weaknesses, and preferences in order to identify and plan for their areas of development.

Development of these skills are key to independent enquiry and self-regulation.

The development of structured self-assessments using the diagnostic tool will allow the students to reflect upon their own levels of confidence linked to key competencies, attributes, and preferences; direct them to a variety of targeted self-access resources, including support, relevant to their levels of confidence; and create space for them to identify their own development plans.

Another wider benefit is that the student response data can also be used to inform future course/resource content development, including any specific student requirements around preferences/needs.

What is it?

The confidence-based self-assessment diagnostic tool provides a mechanism for staff to create bespoke diagnostics, allowing students to align their levels of confidence around the skills, needs, preferences and competencies that they will need on their course (and/or placement or future employment) and to (self) determine a plan of action to develop these skills and competencies along-side their studies using linked resources.

Using the students’ responses, either individually or collectively, can be a useful method to stimulate a formative exchange between the students and tutors.

Diagnostics can be built to accommodate between one and six skills categories assigned/created by you. Each category containing eight confidence-based questions (I can…) assigned/created by you. The students choose a response indicating – high confidence or reasonable confidence or low confidence or don’t know/no experience. All questions are randomised, and category information is not provided until the response page. Based upon the responses given the students are presented with feedback created by you linked to practical suggestions in url links (to workshops, practicums, online resources, drop-ins & courses, et cetera) chosen by you. Students then set their own developmental goals based upon these recommendations.

See Create a Diagnostic for further information of the customisable fields.

Student responses can be set to be anonymised or onymised, in both cases unique users can be identified.

Diagnostics can be deployed to UoB students (or staff), via SSO,  or to external users, via a registration page, for pre-arrival, Widening Participation (WP) et cetera.

The student response data (question responses and areas for development) is available via an inbuilt Response Dashboard, with the raw data available for download in a CSV format.

The diagnostic tool dashboard.

How might I use it?

Students need to have a clear understanding of skills required for their studies, research and/or future employment. By building self-assessments linked to these skills, we can help students to identify their own tailored and unique areas for development and to link these to specific support and resources.

Examples of areas where a diagnostic might be developed

  • supporting students at year-level to ‘signpost’ the skills and attributes that they will need and linking them to support and resources
  • supporting students using labs to ‘signpost ‘ support and resources in areas such as equipment calibration, health and safety, rules and regulations
  • supporting students with non-academic needs to ‘signpost’ support and resources
  • supporting students and staff to ‘signpost’ resources and support around digital capabilities
  • supporting students’ pre-arrival

What are the pros & cons?

  • built with accessibility in mind
  • built to be user-friendly
  • no text editor required to create content
  • simple Content Management Template design
  • device agnostic design – makes it possible to view content on different devices (such as tablets and smartphones)
  • category and question banks are stored openly, for collaboration or sharing
  • URL based content means it can be deployed via any web-based tool – such as Moodle, email, social media
  • diagnostics can be reused
  • co-author assignment to collaboratively build and analyse response data
  • access via SSO (Single Sign-on) for UoB students/staff or via secure registration for external students/staff
  • trackable student data which can be used for research purposes or course evaluations
  • response data available for analysis using both an inbuilt dashboard and exportable cvs file
  • adding more sophisticated text editing requires knowledge/confidence to use Hyper Text Markup Language (HTML), though this is not necessary to develop and deploy a diagnostic

Further reading

  • Stankov, Lazar & Kleitman, Sabina & Jackson, Simon. (2014). Measures of the Trait of Confidence. 10.1016/B978-0-12-386915-9.00007-3.
  • David Boud (2000) Sustainable Assessment: Rethinking assessment for the learning society, Studies in Continuing Education, 22:2, 151-167, DOI: 10.1080/713695728
  • European Parliament, 2008. Skills and competences are further defined in Appendix D.
  • Evers, Frederick T., & S. O’Hara. 1996. ‘Educational Outcome Measures of Knowledge, Skills, and Values by Canadian Colleges and Universities.’ Educational Quarterly Review 3 (1): 43–56.
  • OECD. 2012. AHELO Feasibility Study Report: Volume 1: Design and Implementation: 18. Paris: OECD
  • Higher Education Funding Council for England (HEFCE). 2014a. Review of the National Student Survey: 28. London: HEFCE
  • David Nicol (2009) Assessment for learner self‐regulation: enhancing achievement in the first year using learning technologies, Assessment & Evaluation in Higher Education, 34:3, 335-352, DOI: 10.1080/02602930802255139
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