Tag Archives: Hattie

Summary of SOLO Posts

As one of the searches that seems to bring people to my site is for SOLO taxonomy, here is a post which provides links to each of the posts I have written about SOLO. I am not saying that SOLO is a magic bullet or universal panacea, however, my research suggests that it may have a positive impact.

My advice, for what it’s worth, is: read about it, try it for yourself if you want to and make up your own mind whether it is useful for you and your students.

MA Research Project

All of these posts are based on my final MA dissertation, as a result they tend to be more theoretical.

Teaching with SOLO

These posts are about my own experiences using SOLO in lessons.

If you have any questions, feel free to comment and I’ll do my best to answer.

SOLO, Learning and Teaching

For educators, there is a need to identify how they can best help students to achieve their potential. School makes up a significant part of students’ young lives, so it is unsurprising that:

Schools shape and change beliefs, both as purveyors of knowledge and as epistemological training grounds for developing students. (Schraw, 2001:406)

The challenge is to balance the imparting of knowledge with providing students with opportunities to develop positive epistemological beliefs. New initiatives often focus on the former, specifically teaching methods, possibly because this is an easier area to demonstrate impact. As Hattie (2012) notes, most of what we do as teachers will have some effect on the students we teach.

OfSTED’s (2012/13b:32) definition of an ‘Outstanding’ school highlights the importance of students ‘making and exceeding expected progress’, whatever their starting point. To achieve this, schools need to know what causes variance between students, both between schools and between students in the same school. Hattie (2003) identifies several elements which are responsible for potential variance in achievement. The most significant factor identified was the student themselves, being responsible for 50% of variance. Student engagement, beliefs and motivation is at the heart of the matter.

Levin (2010:89) explains that:

Schools with higher levels of engagement are more successful with students from all kinds of backgrounds.

This supports Hattie’s (2003) findings that home is less significant an influence than perhaps we might expect.

The second most significant influence was the teacher (30%):

It is what teachers know, do and care about which is very powerful in this learning equation. (Hattie, 2003:2)

However, Schraw (2001:406 summarises a key difficulty with addressing the issue:

The existing research invites the conclusion that schools should make the effort to change beliefs in positive ways, although it is less clear how those changes should occur.

Hattie’s work (2003, 2012) may give us an indication of how these changes should be approached; if both students and teachers are responsible for 80% of the variance between student outcomes, it is here that the focus needs to be. Ideally, a focus on techniques and strategies which encourage teachers to teach in the most effective manner, while encouraging students to learn and develop positive epistemological beliefs.

Students’ Learning

To understand how students learn effectively, it is useful to be aware of a number of key areas. Firstly, how do epistemological beliefs affect learning? And secondly, which specific traits does an effective learner have?

 Hofer & Pintrich (1997:88) define personal epistemology as:

How individuals come to know, the theories and beliefs they hold about knowing, and the manner in which such epistemological premises are a part of and an influence on the cognitive processes of thinking and reasoning.

Resent research into students’ beliefs about learning (Pintrich, 2002; Cano & Cardelle-Elawar, 2004; Dweck, 2006; Barnard et al., 2008; Afflerbach et al., 2013) have highlighted the link between how students view learning and their academic performance. Cano & Cardelle-Elawar (2004:182) suggesting that:

The evidence that secondary school students hold immature beliefs…might go some way to explaining the poor academic achievement of many students.

As teachers, we often see this manifested as a willingness to give up when challenged, reluctance to work hard for results and the belief that they are either ‘good’ or ‘bad’ at a particular subject. I know that, in the past, I have been guilty of this, especially with Maths – in reality, I’m not actually bad at Maths, I just find it harder.

However, Louca et al. (2004:58) assert, in their study of teaching science to 3rd grade students, that students are not aware of these ‘beliefs of theories’, but instead ‘have a range of cognitive resources for understanding knowledge’. With many schools implementing ‘learning to learn’ schemes, students are now more likely to have an awareness of how they learn. At the heart of this awareness, there needs to be the belief that learning is complex and requires effort.

An effective student needs to develop a wide range of skills and attributes:

Learning at school requires students to pay attention, to observe, to memorize, to understand, to set goals and to assume responsibility for their own learning. These cognitive activities are not possible without the active involvement and engagement of the learner. (Vosniadou, 2001:8)

The emphasis, for effective learning and progress to take place, is on the need for students to be self-regulated (Barnard et al., 2008; Nückles et al., 2009; Afflerbach et al., 2013) and for students to have some control over their learning (Skinner et al., 1998, cited in Yeh, 2010; Vosniadou, 2001; Zull, 2002).

What Makes a Teacher Effective?

Researchers and policymakers have often tried to define what makes an effective teacher; however arriving at a definition can be fraught with difficulties. Shulman (1987:6) notes that these definitions often ‘became items on tests or on classroom-observation scales’ which ultimately end up as a restrictive check-list. Levin (2010:90) points out that, proposals for improving teaching ‘have been made many times before’ and that merely listing suggestions is not enough – we need concrete examples of how this might be achieved.

Although our knowledge of how the brain works has developed over the past century, the topic can be a contentious one. Information processing, ‘the mental operations that come between a stimulus and response’ (Malim & Birch, 2005:25), is at the centre of discussion between cognitive psychologists, especially when related to student learning (Vygotsky, 1978 cited in Vosniadou, 2001; Kolb, 1984; Baddeley, 1999; Bischoff & Anderson, 2001; Tsai & Huang, 2001). Kirschner et al. (2006:77) highlight the importance of an understanding of the brain’s processes:

Any instructional theory that ignores the limits of working memory when dealing with novel information, or ignores the disappearance of those limits when dealing with familiar information, is unlikely to be effective.

 As a result of the complexities, and lack of a definitive explanation of how the brain works, there have been disagreements between academics as to the best mode of instruction, in particular between project based learning and direct instruction (Bishoff & Anderson, 2001; Wallace & Louden, 2003; Gauthier & Dembélé, 2004; Zull, 2002; Wu & Tsai, 2005; Kirschner et al., 2006; Hmelo-Silver et al., 2007; Granger et al., 2012; Hodges, 2012). These discussions can become polarised, while the most effective teaching is likely to judiciously use elements from both modes.

However, there also appear to be several areas of agreement; Hattie (2012:16) states that:

The act of teaching requires deliberate interventions to ensure that there is cognitive change in the student; thus the key ingredients are being aware of the learning intentions, knowing when a student is successful in attaining those intentions, having sufficient understanding of the student’s prior understanding as he or she comes to the task and knowing enough about the content to provide meaningful and challenging experiences so that there is some sort of progressive development.

This suggests that an in depth knowledge of the students is one of the hallmarks of an effective teacher. In addition, we can add: high expectations (Levin, 2010; OfSTED, 2012), formative assessment (Black & Wiliam, 2006), differentiation (Hattie, 2003; Yeh, 2010; Hook & Mills, 2012; OfSTED, 2012) and feedback (Hattie, 2003, 2012; Black & Wiliam, 2006; OfSTED, 2012). The SOLO taxonomy can offer teachers a structure for implementing these skills in conjunction with the teacher’s existing strategies.


Afflerbach, P., Cho, B-Y., Kim, J-Y., Crassas, M., & Doyle, B. (2013) ‘Reading: What else matters besides strategies and skills?’ The Reading Teacher, 66 (6), pp. 440–448. Available at: http://doi.wiley.com/10.1002/TRTR.1146 [Accessed March 2, 2013].

Baddeley, A. D. (1999) Essentials of Human Memory. Hove: Psychology Press

Barnard, L., Lan, W., Crooks, S., & Paton, V. (2008) ‘The relationship between epistemological beliefs and self-regulated learning skills in the online course environment’. MERLOT Journal of Online Learning and Teaching 4 (3) pp. 261-266

Bischoff, P.J. & Anderson, O.R. (2001) ‘Development of knowledge frameworks and higher order cognitive operations among secondary school students who studied a unit on ecology’. Journal of Biological Education 35 (2), pp. 81-88.

Black, P. & Wiliam, D., 2009 ‘Developing the theory of formative assessment’ J. Gardiner, ed. Educational Assessment Evaluation and Accountability, 1 (1), pp. 5–31. Available at: http://eprints.ioe.ac.uk/1119/. [accessed 23 August 2012]

Cano, F. & Cardelle-Elawar, M. (2004) ‘An integrated analysis of secondary school student’s conceptions and beliefs about learning’. European Journal of Psychology of Education 19 (2) pp. 167-187.

Dweck, C. (2006) Mindset: The New Psychology of Success. New York: Random House.

Gauthier, C. & Dembélé, M. (2004) ‘Quality of teaching and quality of education: a review of research findings. UNESCO. Education for All Global Monitoring Report. 2005/ED/EFA/MRT/PI/18

Granger, E. M., Bevis, T. H., Saka, Y., Southerland, S. A., Sampson, V., & Tate, R. L. (2012) ‘The efficacy of student-centered instruction in supporting science learning’. Science (New York, N.Y.), 338 (6103), pp. 105–8. Available at: http://www.ncbi.nlm.nih.gov/pubmed/23042893 [Accessed March 11, 2013].

Hattie, J. (2003) Teachers make a difference: what is the research evidence? Melbourne: Australian Council for Educational Research

Hattie, J. (2012) Visible Learning for Teachers: Maximizing Impact on Learning. Abingdon: Routledge

Hmelo-Silver, C. E., Duncan, R.G. & Chinn, C. A. (2007) ‘Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006)’. Educational Psychologist  42 (2) pp. 99–107. Available at: http://www.tandfonline.com/doi/abs/10.1080/00461520701263368.

Hodges, G. C., (2012) ‘Research and the teaching of English: Spaces where reading histories meet’. English Teaching: Practice and Critique 11 (1), pp. 7–25.

Hofer, B., & Pintrich, P. (1997) ‘The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning’. Review of Educational Research 67 (1) pp. 88-140.

Hook, P. & Mills, J. (2012) SOLO Taxonomy: A Guide for Schools Book 2: Planning for differentiation. Laughton, UK: Essential Resources Educational Publishers

Kirschner, P.A., Sweller, J. & Clark, R.E. (2006) ‘Work : An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching’. Learning  41 (2), pp. 75–86. Available at: http://www.informaworld.com/openurl?genre=article&doi=10.1207/s15326985ep4102_1&magic=crossref.

Kolb, D. A. (1984) Experiential Learning: experience as the source of learning and development. New Jersey: Prentice-Hall

Levin, B. (2010) ‘What did you do at school today?’ Kappan. 91 (5) pp. 89-90. http://www.education.auckland.ac.nz/webdav/site/education/shared/about/centres/uacel/docs/InCanadaWDYDIST1002lev.pdf [accessed 8 April 2012]

 Louca, L., Elby, A., Hammer, D., & Kagey, T. (2004) ‘Epistemological resources: Applying a new epistemological framework to science instruction’. Educational Psychologist 39 (1) pp. 57-68.

Malim, T., & Birch, A. (2005) Introductory Psychology. Baisingstoke: Palgrave Macmillan

OfSTED (2012/13a) The framework for school inspection. HMI 120100. London: OfSTED publications.  http://www.ofsted.gov.uk/resources/framework-for-school-inspection [accessed 15 April 2013]

OfSTED (2012/13b) School Inspection Handbook. HMI 120101. London: OfSTED publications.  http://www.ofsted.gov.uk/resources/school-inspection-handbook  [accessed 15 April 2013]

Pintrich, P. (2002) Future challenges and directions for theory and research on personal epistemology. In B. Hofer and P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp.389-414). Mahwah, New Jersey: Lawrence Erlbaum Associates.

Schraw, G. (2001) ‘Current themes and future directions in epistemological research: A commentary.’ Educational Psychology Review. 13 (4) pp. 451-464.

Shulman, L.S., (1987) ‘Knowledge and Teaching: Foundations of the New Reform’. Harvard Educational Review, 57 (1), pp. 1–21.

Tsai, C-C. and Huang, C-M. (2001) ‘Development of cognitive structures and information processing strategies of elementary school students learning about biological reproduction’. Journal of Biological Education 36 (1) pp. 21-26.

Vosniadou, S. (2001) How Children Learn. UNESCO. Educational Practices Series 7. http://www.ibe.unesco.org/fileadmin/user_upload/archive/publications/EducationalPracticesSeriesPdf/prac07e.pdf [accessed 12 December 2012]

Wallace, J. & Louden, W. (2003) ‘What we don’t understand about teaching for understanding: questions from science education’, Journal of Curriculum Studies, 35, 5 pp. 545-566

Wu, Y-T. and Tsai, C-C. (2005) ‘Effect of Constructivist Oriented Instruction on Elementary School Students’ Cognitive Structures’. Journal of Biological Education 39 (3), pp. 113-119.

Yeh, S. (2010) ‘Understanding and addressing the achievement gap through individualized instruction and formative assessment.’ Assessment in Education: Principles, Policy & Practice 17 (2) pp. 169-182

Zull, J. (2002). The Art of Changing the Brain: Enriching the Practice of Teaching by Exploring the Biology of Learning. USA: Stylus Publishing.

What is the SOLO Taxonomy?

Learning taxonomies and frameworks are researchers’ and theorists’ attempts to categorise and explain learning (Bloom, 1956; Anderson, et al., 2000; Moseley, et al., 2005). These frameworks help teachers gain an insight into how students think and learn, however, due to the complexities of the human brain, they can only be used as a guideline. As our knowledge of the human mind develops, so will the frameworks used to explain the structure of thinking and learning.

In education, Bloom’s (1956) taxonomy, in its original form and as updated by Anderson et al. (2000), is probably the most familiar, examination questions often follow the hierarchy. However, it is not without its problems. Sugrue (2002:1) points out that the original taxonomy ‘was developed before we understood the cognitive processes involved in learning and performance’, and criticises the ‘consistency’ with which it can be applied. Teachers can avoid these problems through an awareness of alternative taxonomies, for example the SOLO taxonomy (Hattie & Brown, 2004).

SOLO (the Structure of the Observed Learning Outcomes) taxonomy was first introduced by Biggs & Collis in their 1982 study. The SOLO taxonomy maps the complexity of a student’s work by linking it to one of five phases:  little or no understanding (Prestructural), through a simple and then more developed grasp of the topic (Unistructural and Multistructural), to the ability to link the ideas and elements of a task together (Relational) and finally (Extended Abstract) to understand the topic for themselves, possibly going beyond the initial scope of the task (Biggs & Collis, 1982; Hattie & Brown, 2004). In their later research into multimodal learning, Biggs & Collis noted that there was an ‘increase in the structural complexity of their [the students’] responses’ (1991:64).

It may be useful to view the SOLO taxonomy as an integrated strategy, to be used in lesson design, in task guidance and formative and summative assessment (Smith & Colby, 2007; Black & Wiliam, 2009; Hattie, 2009; Smith, 2011). The structure of the taxonomy encourages viewing learning as an on-going process, moving from simple recall of facts towards a deeper understanding; that learning is a series of interconnected webs that can be built upon and extended. Nückles et al., (2009:261) elaborates:

Cognitive strategies such as organization and elaboration are at the heart of meaningful learning because they enable the learner to organize learning into a coherent structure and integrate new information with existing knowledge, thereby enabling deep understanding and long-term retention.

This would help to develop Smith’s (2011:92) ‘self-regulating, self-evaluating learners who were well motivated by learning.’

 A range of SOLO based techniques exist to assist teachers and students. Use of constructive alignment (Biggs & Tang, 2009) encourages teachers to be more explicit when creating learning objectives, focusing on what the student should be able to do and at which level. This is essential for a student to make progress and allows for the creation of rubrics, for use in class (Black & Wiliam, 2009; Nückles et al., 2009; Huang, 2012), to make the process explicit to the student. Use of HOT (Higher Order Thinking) maps (Hook & Mills, 2011) can be used in English to scaffold in depth discussion, encouraging students to:

Develop interpretations, use research and critical thinking effectively to develop their own answers, and write essays that engage with the critical conversation of the field (Linkon, 2005:247, cited in Allen, 2011).

It may also be helpful in providing a range of techniques for differentiated learning (Anderson, 2007; Hook & Mills, 2012).

 The SOLO taxonomy has a number of proponents. Hook & Mills (2011:5) refer to it as ‘a model of learning outcomes that helps schools develop a common understanding’. Moseley et al. (2005:306) advocates its use as a ‘framework for developing the quality of assessment’ citing that it is ‘easily communicable to students’. Hattie (2012:54), in his wide ranging investigation into effective teaching and ‘visible learning’, outlines three levels of understanding: surface, deep and conceptual. He indicates that:

The most powerful model for understanding these three levels and integrating them into learning intentions and success criteria is the SOLO model.

 However, the taxonomy is not without detractors; Chick (1998:20) believes that ‘there is potential to misjudge the level of functioning’ and Chan et al. (2002:512) criticises its ‘conceptual ambiguity’ stating that the ‘categorization’ is ‘unstable’. In these two studies, the SOLO taxonomy was used primarily for assessing completed work, so use throughout the teaching process may mitigate these issues.

 An additional criticism, in particular when the taxonomy is compared with that of Bloom (1956), is the SOLO taxonomy’s structure. Biggs & Collis (1991) refers to the structure as a hierarchy, as does Moseley et al. (2005); naturally, there are concerns when complex processes, such as human thought, are categorized in this manner. However, Campbell et al. (1992) explained the structure of the SOLO taxonomy as consisting as a series of cycles (especially between the Unistructural, Multistructural and Relational levels), which would allow for a development of breadth of knowledge as well as depth.

Allen, I. J., (2011) ‘Reprivileging reading: The negotiation of uncertainty’. Pedagogy: Critical Approaches to Teaching Literature, Language, Composition, and Culture, 12 (1) pp. 97–120. Available at: http://pedagogy.dukejournals.org/cgi/doi/10.1215/15314200-1416540 [Accessed March 26, 2013].

Anderson, K. M., (2007) ‘Differentiating instruction to include all students’. Preventing School Failure, 51 (3) pp. 49–54.

Anderson, L. W., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2000) A Taxonomy for Learning, Teaching, and Assessing: A revision of Bloom’s Taxonomy of educational objectives. New York: Pearson, Allyn & Bacon.

Biggs, J. & Tang, C. (2009) ‘Applying constructive alignment to outcomes-based teaching and learning.’ Training Material. “Quality Teaching for Learning in Higher Education” Workshop for Master Trainers.  Ministry of Higher Education. Kuala Lumpur. 2010. http://drjj.uitm.edu.my/DRJJ/MQAGGPAS-Apr2011/What-is-CA-biggs-tang.pdf [accessed 19 August 2012]

Biggs, J. B. and Collis, K. F. (1982) Evaluating the Quality of Learning: the SOLO taxonomy. New York, Academic Press

Biggs, J. B., & Collis, K .F. (1991) ‘Multimodal learning and the quality of intelligent behaviour’. In: H. Rowe (Ed.) Intelligence: Reconceptualization and measurement.  Hillsdale, NJ.:  Lawrence Erlbaum. pp. 57-75.

Black, P. & Wiliam, D., 2009 ‘Developing the theory of formative assessment’ J. Gardiner, ed. Educational Assessment Evaluation and Accountability, 1 (1), pp. 5–31. Available at: http://eprints.ioe.ac.uk/1119/. [accessed 23 August 2012]

Bloom, B. S. (1956) Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain. New York: David McKay Co Inc.

Campbell, K. J., Watson, J. M., & Collis, K. F. (1992) ‘Volume measurement and intellectual development’. Journal of Structural Learning. 11  pp. 279-298.

Chan, C.C., Tsui, M.S. & Chan, M.Y.C., 2002 ‘Applying the Structure of the Observed Learning Outcomes ( SOLO ) taxonomy on student’s learning outcomes : an empirical study’. Assessment and Evaluation in Higher Education 27 (6) pp. 511-527

Chick, H. (1998) ‘Cognition in the Formal Modes: Research mathematics and the SOLO taxonomy’. Mathematics Education Research Journal. 10 (2) pp. 4-26

Hattie, J. (2003) Teachers make a difference: what is the research evidence? Melbourne: Australian Council for Educational Research

Hattie, J. (2009) Visible Learning. New York: Routledge

Hattie, J. (2012) Visible Learning for Teachers: Maximizing Impact on Learning. Abingdon: Routledge

Hattie, J. & Brown, G. (2004) ‘Cognitive processes in asTTle: The SOLO taxonomy.’ University of Auckland/Ministry of Education. asTTle Technical Report 43. http://e-asttle.tki.org.nz/content/download/1499/6030/version/1/file/43.+The+SOLO+taxonomy+2004.pdf [accessed 6 March 2013]

Hook, P. & Mills, J. (2011) SOLO Taxonomy: A Guide for Schools Book 1: A common language of learning. Laughton, UK: Essential Resources Educational Publishers

Huang, S.-C. (2012) ‘Like a bell responding to a striker: Instruction contingent on assessment’. English Teaching: Practice and Critique 11 (4), pp. 99–119.

Moseley, D., Baumfield, V., Elliott, J., Gregson, M., Higgins, S., Miller, J., & Newton, D. (2005) Frameworks for Thinking: A handbook for teaching and learning. Cambridge: Cambridge University Press

Nückles, M., Hübner, S. & Renkl, A. (2009) ‘Enhancing self-regulated learning by writing learning protocols’. Learning and Instruction, 19(3), pp.259–271. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0959475208000558 [Accessed March 26, 2013].

Smith, A. (2011) High Performers: The Secrets of Successful Schools. Camarthen: Crown House Publishing

Smith, T.W. & Colby, S.A. (2007) ‘Teaching for Deep Learning.’ The Clearing House.  80 (5) pp. 205–211.

Sugrue, B. (2002) ‘Problems with Bloom’s Taxonomy.’ http://eppicinc.files.wordpress.com/2011/08/sugrue_bloom_critique_perfxprs.pdf [accessed 2 May 2013]