Literature review of assessment and reporting on the affective domain
Literature examining education reform exposes a pressing need for review of current assessment practices and school evaluation in order to improve school performance (Masters, 2013). Evaluation draws on a continuum paradigm rather than simple measurement; the problematic black box of education is finding out about students’ learning (Black & Wiliam, 1998).
With assessment situated at the heart of learning – and, by extension, the school as a learning organisation – research shows that purposeful and planned strategies ensuring accurate interpretations of student growth inform improvements. For the purposes of this review, the affective domain is defined as growth in feelings or emotional areas, as distinct from cognitive or psychomotor skills (Krathwohl, Bloom & Masia, 1973). Challenges arise in monitoring specific features of the affective domain since measurement instruments focus on students’ understandings or behaviour; teacher inferences are seen as problematic, and caution is advised when generalising about wellbeing from evidence of social and emotional growth (Forster, 2004).
While studies of best assessment practices are broad (Barber & Mourshed, 2007; Hattie, 2009), policymakers are enthusiastic (CRESST, 2011), case study findings vary (Broadfoot & Black, 2004), and theorists differ in their analyses of how improvement in performance is achieved, selectivity yields a balanced perspective in the school context. Characteristic of the research, more accurate interpretation of student growth through best assessment practice is defined as a process of visible learning (Hattie, 2009) which is attained by setting clear and high expectations for what students should achieve (Barber & Mourshed, 2007; Marzano, Pickering & Pollock, 2001; Sharratt & Fullan, 2012). Commonality emerges in studies emphasising the significance of feedback which is seen as the vital link between teaching and learning (Hattie, 2003; Wiliam, 2011), and facilitates a means of opening the black box to closer scrutiny (Black & Wiliam, 1998).
Specific difficulty assessing the affective domain is emphasised in relation to obtaining objective, valid and reliable measures of student achievement (Worrell, Evans-Fletcher & Kovar, 2013). Additionally, many teachers are identified as focusing on assessment of the cognitive domain, whereas physical education teachers have been criticised for restricting their grading of the affective domain to participation (Holt & Hannon, 2006).
Overcoming perceived neglect seems reliant on all teachers developing understanding of the importance of social and emotional skills in order to more effectively write clear objectives which are then made explicit to students during assessment for learning. According to the research, specifically identifying steps and tools to create affective assessment processes such as checklists, rubrics and rating scales will assist in
creating purposeful and engaging learning opportunities… to guide students toward critical learning outcomes (Glennon, Hart & Foley, 2015, p.44).
In order to effect change in the classroom, research indicates that school leaders bridge dichotomies to make nuanced judgements about leading best practice with staff in their school context by driving an explicit improvement agenda (CRESST report 802, 2011; Masters, 2010). This process is underscored by an important credo – “know students and how they learn” (AITSL, 2011, p.9) – thus demanding considered integration of three overlapping concepts:
- Formative assessment practice;
- school and system level evaluation; and
- principles of educational measurement.
Central issues or concerns relate to scale, context and reliability of data. Care is essential to interpret data and drive improvements in learning:
When teachers are provided with opportunities to use and interpret assessment data in order to become more responsive to their students’ learning needs, the impact is substantive. Teachers, however, cannot do this alone, but require system conditions that provide and support these learning opportunities in ways that are just as responsive to how teachers learn as they are to how students learn (Timperley, 2009, p. 24).
For reasons of complexity, effectively evaluating data demands that professional on-balance judgements hold sway. While there are lessons to be learned from why some school systems succeed and others do not (Barber & Mourshed, 2007), school and system level evaluation affords only broad classifications of student performance.
By manipulating the lens through which we view local, school-based, learner-focused growth processes, meaning is effectively contextualised. Focusing attention on how assessment is used rather than its primary purpose or context,
brings together research underpinning ‘assessment for learning’ with research on high performing school systems; how students learn and highly effective teachers (Forster, 2009, p. 5).
Studies show it is necessary to log events, such as students engaged in “self-assessing, self-evaluating, self-monitoring, self-learning” (Hattie, 2009, p. 37) in order to build hypotheses, foster considered interpretation of fine-grained assessment data, and render both objectives and success criteria visible. Operating within a unified sphere where assessments are deliberately constructed, data are generated and inferences drawn to drive school improvement, system level evaluation and principles of educational measurement can effectively serve as a supportive conceptual framework to sustain best assessment practices.
AITSL. (2011). National Professional Standards for Teachers. Retrieved March 17, 2017 from Australian Institute for Teaching and School Leadership website: http://www.aitsl.edu.au/docs/default-source/apst-resources/australian_professional_standard_for_teachers_final.pdf
Barber, M. & Mourshed, C.C. (2007). How the world’s best performing school systems come out on top. Retrieved January 25 from McKinsey & Company: http://mckinseyonsociety.com/how-the-worlds-best-performing-schools-come-out-on-top/
Black, P. & Wiliam, D. (1998). Inside the black box: Raising standards through classroom achievement. Retrieved March 16 2017 from: https://weaeducation.typepad.co.uk/files/blackbox-1.pdf
Broadfoot, P. & Black, P. (2004). Redefining assessment: The first ten years of Assessment in Education. Assessment in education: Principles, policy & practice, 11(1), 7-26. Retrieved from ProQuest.
CRESST report 802. (2011). Knowing and doing: What teachers learn from formative assessment and how they use information. Retrieved March 18 2017 from: http://cresst.org/publications/cresst-publication-3172/
Forster, M. (2004). Measuring the social outcomes of schooling: What does ACER research tell us? Retrieved March 3 2017 from: http://research.acer.edu.au/cgi/viewcontent.cgi?article=1004&context=research_conference_2004
Forster, M. (2009). Informative assessment: Understanding and guiding learning. Paper presented at the ACER research conference on Assessment and Student Learning. Retrieved March 9 2017 from: http://research.acer.edu.au/cgi/viewcontent.cgi?article=1040&context=research_conference
Glennon, W., Hart, A. & Foley, J.T. (2015). Developing effective affective assessment practices. The Journal of Physical Education, Recreation & Dance, 86(6), 40-44.
Hattie, J. (2003). Teachers make a difference: What is the research evidence? Retrieved March 16 from: http://research.acer.edu.au/cgi/viewcontent.cgi?article=1003&context=research_conference_2003
Hattie, J. (2009). Visible learning. Oxon: Routledge.
Holt, B.J. & Hannon, J.C. (2006). Teaching learning in the affective domain. Strategies, A Journal for Physical and Sport Educators, 20(1), 11-13.
Krathwohl, D.R., Bloom, B.S., & Masia, B.B. (1973). Taxonomy of educational objectives, the classification of educational goals. Handbook II: Affective domain. New York: David McKay Co., Inc.
Masters, G.N. (2010). Teaching and learning school improvement framework. Retrieved March 18, 2017 from ACER website: http://research.acer.edu.au/cgi/viewcontent.cgi?article=1015&context=monitoring_learning
Masters, G.N. (2013). Reforming educational assessment: Imperatives, principles and challenges. Camberwell, Victoria: Australian Council for Educational Research.
Marzano, R.J., Pickering, D.J., & Pollock, J.E. (2001). Classroom instruction that works: Research based strategies for increasing student achievement. Upper Saddle River, NJ: Pearson.
Sharratt, L. & Fullan, M. (2012). Putting faces on the data: What great leaders do. Thousand Oaks, CA: Corwin.
Timperley, H. (2009). Using assessment data for improving teaching practice. Retrieved February 9 from: http://research.acer.edu.au/cgi/viewcontent.cgi?article=1036&context=research_conference
Wiliam, D. (2011). Embedded formative assessment. Bloomington, IN: Solution Tree Press.
Worrell, V., Evans-Fletcher, C. & Kovar, S. (2013). Assessing the cognitive and affective progress of children. Journal of Physical Education, Recreation & Dance, 73(7), 29-34.