This page explores the different theoretical models and taxonomies that underpin how students learn, and therefore how we should structure teaching, learning and assessment.

Bloom’s Taxonomy

What is it? 

Bloom’s Taxonomy was originally developed by educational psychologist Benjamin Bloom (Bloom, et al 1956), with the first version published in the early 1950s and a major revision by David Krathwolh released in 2002. 

The taxonomy organises educational learning goals into hierarchies according to what ‘domain’ the learner is using, along with how complex or specific a learning task is. The taxonomy divides learning objectives into groups, which target three main dimensions of learning: 

  1. cognitive domain, i.e. the intellectual/knowledge-oriented part of learning; 
  2. affective domain, i.e. learning which targets attitudes and emotions; and
  3. psychomotor domain, i.e. action-based learning.

Bloom's Revised Taxonomy

Source: Bloom's Revised Taxonomy, Vanderbilt University Center for Teaching,

Why use it?

If you have ever taught or studied formally, you will very likely have encountered Bloom’s Taxonomy. Bloom’s Taxonomy is used extensively within educational settings worldwide and is a foundational theory in the Australian higher education system. Most learning objectives/outcomes and assessments are designed around the taxonomy. Therefore, it is important to have an understanding of what it is and its application. 

How to use it?

Bloom’s Taxonomy can be used to:

  • set learning goals and plans
  • create/revise learning objectives
  • match learning objectives to new or existing learning activities
  • build multi-layer learning activities
  • create assessments and assess their level of difficulty for learners
  • plan lessons/ develop online/face to face learning content
  • provide opportunities for learners and teachers to reflect on progress.

(Persaud, 2021)

Learning activities can be built based on how quickly learners can take up new concepts, when they should receive reinforcement of concepts, and when and how to test their learning. Bloom’s taxonomy translates into a series of verbs used to design learning objectives/activities/assessments. For example, ‘analyse quantitative and qualitative research data using appropriate software tools’ or ‘identify the most appropriate research methods and practices for specific research contexts’.

The taxonomy has some limitations. It is based on assumptions that:

  • learning is sequential (i.e. remembering comes before understanding),
  • hierarchical (evaluating is a higher order/more valuable skill than understanding) (Lawler, 2016), and
  • ordered by nature (i.e. there are clear distinctions between cognitive learning processes) (Fadul, 2009).

The way the taxonomy is implemented across different academic institutions also varies, so there are no consistent learning outcomes to map verbs.

Find out more

Bloom’s taxonomy website -

Bloom’s taxonomy free downloadable guide -

Bloom, B. S.; Engelhart, M. D.; Furst, E. J.; Hill, W. H.; Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York: David McKay Company.

Derek Box Center for Teaching and Learning, Harvard University, Taxonomies for learning

Krathwohl, David R. (2002). "A revision of Bloom's taxonomy: An overview". Theory into Practice. Routledge. 41 (4): 212–218. doi:10.1207/s15430421tip4104_2. ISSN 0040-5841. S2CID 13116159.

Persaud, C. (2021). Bloom’s Taxonomy: The Ultimate Guide. Top Hat Blog. Retrieved from on 8 June, 2021.

Lawler, S. (26 February 2016). "Identification of animals and plants is an essential skill set". The Conversation. Archived from the original on 17 November 2016. Retrieved 8 June 2021.

Fadul, J. A. (2009). "Collective Learning: Applying distributed cognition for collective intelligence". The International Journal of Learning. 16 (4): 211–220. doi:10.18848/1447-9494/CGP/v16i04/46223. ISSN 1447-9494.

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Marzano’s New Taxonomy

What is it? 

Marzano’s New Taxonomy characterises lower-order thinking skills as those for accessing and making sense of ‘existing’ knowledge. In contrast, higher-order thinking skills were involved in the eliciting and creation of ‘new’ knowledge (Dubas & Toledo, 2016).

Developed by educational researcher, Robert Marzano, Marzano’s Taxonomy (2000) was a response to shortcomings he identified in the ‘Bloom’s taxonomy of learning’. Both taxonomies provide a structural hierarchy for lower-order ‘surface learning’ and higher-order ‘deep learning’ thinking.

However, Marzano states that his taxonomy outlines how the learner treats a task, in being:

  1. a flow of processing and information, and
  2. the level of consciousness required to control execution (Irvine, 2017). 

Marzano’s Taxonomy comprises three systems and a knowledge domain. 

The three systems are the:

  1. Self-system. The self-system considers the beliefs about the importance of knowledge, beliefs about efficacy, and emotions associated with knowledge.
  2. Metacognitive system. The metacognitive system focuses on specifying learning goals, monitoring the execution of knowledge, monitoring clarity, and monitoring accuracy.
  3. Cognitive system (which is somewhat similar to Bloom’s lower and higher-order thinking framework). The cognitive system is broken down into four areas: knowledge retrieval, comprehension, analysis, and knowledge utilisation.

The knowledge domain addresses the areas of information, mental procedures, and physical procedures (, 2007).

Why use it?

Marzano’s Taxonomy is considered to be a useful alternative framework to Bloom’s Revised Taxonomy, to serve as a useful framework approach to course design for drafting student learning outcomes (SLOs), creating assessment, and for providing more targeted feedback. This Taxonomy helps us think more seriously about the cognitive demands we place on students when asking questions and building understanding; placing emphasis on the thought process rather than the task or question (Dubas & Toledo, 2016). Marzano’s Taxonomy also considers how we may more appropriately scaffold instruction, to break up a task into smaller chunks to reduce cognitive load, and monitor information processing levels. It also addresses ways in which we can monitor a student’s progress toward meeting their goals (Dubas & Toledo, 2016).

How to use it?

1. For designing Student Learning Objectives (SLOs)

In the course design process, Student Learning Outcomes (SLOs) for each predetermined content-based Knowledge-Focus (KF) area can be developed according to the cognitive level in Marzano’s taxonomy. We do this by identifying the most appropriate cognitive level to target for each KF. This approach allows us to categorize and identify the types of thinking processes we want students to engage in in the transfer of knowledge and engagement in higher-order thinking; this is purely at the discretion of the instructor. This approach also allows us to think about scaffolding – if we are intentionally thinking about what students should know and the cognitive level required, then it enables us to think about the specific steps required in the process of instruction that is needed to have students reach the desired level of mastery for that KF area.

2. For use with learning task types such as multiple-choice questions

As Marzano’s Taxonomy is a more comprehensive framework of lower and higher-order thinking skills, it is useful to utilise the wide range of thinking skills available for use with learning task types. For example, in a task that contains multiple-choice questions, it would be useful to address a specific thinking skill for use with each question.

3. To include and evaluate a student’s ability to plan and think about their learning

Marzano’s Taxonomy expands on Bloom’s Taxonomy to address learner self-efficacy and the metacognitive system. The former could consider how the learner self-regulates and goes about prioritising information and tasks in the learning process. The metacognitive system includes specifying goals, process monitoring, and monitoring clarity and accuracy. These aspects can be incorporated in activity plans, that require the learner to plan their approach to undertaking a learning task, how they manage their understandings in the learning process (self-reflection and thinking deeply about their own learning), and their ability to check their own information accuracy in the process. This also helps learners to be involved in undertaking strategies that they can apply as skills in the future.

Find out more

Intel Teach Program (2012) Marzano’s New Taxonomy

Dubas, J. & Toledo, S. (2016). Taking higher-order thinking seriously: Using Marzano’s taxonomy in the economics classroom, International Review of Economics Education, 21.

Irvine, J. (2017). A Comparison of Revised Bloom and Marzano's New Taxonomy of Learning. Research in Higher Education Journal, 33. (2007). Designing effective projects: Thinking skills frameworks. Marzano’s taxonomy.

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SOLO Taxonomy

What is it?

Biggs and Collins (1982) developed the SOLO (Structure of Observed Learning Outcomes) Taxonomy as a systematic way of describing how a learner’s performance grows in complexity when mastering tasks. Performance levels of learners range from the lower end (Pre-structural) to the higher end (Extended abstract) as shown in the diagram below.

SOLO Taxonomy

Diagram: SOLO Taxonomy (Biggs: 2003: 48)

Pre-structural level

The student does not have any kind of understanding, uses irrelevant information and/or misses the point altogether

Uni-structural level

The student can deal with one single aspect and make obvious connections. The student can use terminology, recite (remember things), perform simple instructions/algorithms, paraphrase, identify, name or count.

Multi-structural level

The student can deal with several aspects but these are disconnected. He/she is able to enumerate, describe, classify, combine, apply methods, structure, execute procedures, etc.

Relational level

The student may understand relations between several aspects and how they might fit together to form a whole. The understanding forms a structure and may thus have the competence to compare, relate, analyse, apply theory, explain in terms of cause and effect.

Extended abstract level

The student may generalise structure beyond what was given, may perceive structure from many different perspectives and transfer ideas to new areas. He/she may have the competence to generalise, hypothesise, criticise or theorise.

How to use it

SOLO can be applied during the course design process when you’re articulating your Intended Learning Outcomes and mapping these to the assessment items and course learning activities.

The following table provides examples of the measurable, active verbs you can use to describe performance at SOLO levels 2–5.

SOLO level Verbs

SOLO 2: Unistructural

Define, identify, name, draw, find, label, match, follow a simple procedure

SOLO 3: Multistructural

Describe, list, outline, complete, continue, combine, calculate

SOLO 4: Relational

Sequence, classify, compare and contrast, explain (cause and effect), analyse, form an analogy, organise, distinguish, question, relate, apply, describe

SOLO 5: Extended abstract

Generalise, predict, evaluate, reflect, hypothesise, theorise, create, prove, justify, argue, compose, prioritise, design, construct, perform, explain, apply, analyse

The following is an example of the Intended Learning Outcomes (ILOs) written for a biology class using the SOLO taxonomy. (Note: the term Intended Learning Outcomes is interchangeable with the terms Learning Outcomes and Learning Objectives).

At the end of the course, the student is expected to be able to:

  • calculate (SOLO 2) recombination frequencies, segregation ratios, inbreeding coefficients, Hardy- Weinberg frequencies, evolutionary equilibria, heritabilities, etc.
  • explain (SOLO 4) and apply (SOLO 3) linkage analysis, including mapping of genes on chromosomes - describe (SOLO 3) and analyse (SOLO 4) simple patterns of inheritance (i.e. through analysis of pedigrees)
  • describe (SOLO 3) and explain (SOLO 4) the concepts of genetic variation, mutation, inbreeding, genetic drift, and natural selection
  • describe (SOLO 3) and explain (SOLO 4) evolutionary processes
  • analyse (SOLO 4) the inheritance at several genes simultaneously
  • explain (SOLO 4) how inbreeding and population mixture influence genetic structure.

(Adapted from Brabrand & Dahl, 2009).


While the SOLO taxonomy can help identify levels of progression with learning, Biggs (1999) also identifies characteristics of students that signal whether they are adopting a deep or surface-level approach to learning. The document: Characteristics of Deep and Surface Approaches to Learning from the University of New South Wales may be helpful in deciding deep or surface-level approaches.

Find out more

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

Biggs, J. (1999). Teaching for Quality Learning at University. SHRE and Open University Press.

Brabrand, C., & Dahl, B. (2009). Using the SOLO taxonomy to analyze competence progression of university science curricula. Higher Education, 58(4), 531-549.

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Need help?

ITaLI offers personalised support services across various areas including using learning taxonomies to inform the design of curriculum, learning activities and assessment.