ACM Inroads: Archive

Today's global computing curricula is seeing an increasing move towards 'competency' rather than the historically 'knowledge-based' computing curricula. "In the CC2020 Report [5] and related work [4,6,8], the notion of competency has been defined as comprising 'knowledge + skills + dispositions + task', based on a broad conception of competency as effective professional performance in a relevant setting." [7]

But does adopting the notion of "skills," drawn from Bloom's cognitive taxonomy here [1,2], fully address the level of all these elements of a competency? This column aims to explore how fully the competencies of CC2020, the Bloom taxonomy of 'skills' from the cognitive domain, and the notion of 'dispositions' really dovetail and what alternative conceptions might be useful?

This question has arisen for me in co-supervising with Dr. Ramesh Lal our student Johnny He's Research Report towards his Master of Computer and Information Sciences. Johnny has sought to contrast how "Skills Requirements" [or capabilities or competencies] for practitioners develop in the transition from Junior Software Developer to Senior Developer. The study has been based on his review of job advertisements and contrasting stated junior and senior software developer expectations. In developing competency statements from this data source, drawing on the process for mapping the knowledge based CS2013 curriculum statements to competency statements, as adopted in the ITiCSE working report [6], two key insights were derived.

for professional skills such as "teamwork" (which did not easily fit within a cognitive taxonomy) Johnny struggled to map them to the "skills" aspect of the identified competency so rated them at level 0 of the "skills" taxonomy; and
in subsequently allocating dispositions, distinguishing between skills element of the CC2020 competency model and junior and senior expectations of the degree of exhibition of a disposition has posed some challenges.

At this point we need to revisit the early work of Bloom and colleagues [1,2,3] in developing educational taxonomies. The "original plans called for a complete taxonomy in three major parts - the cognitive, the affective, and the psychomotor domains. The cognitive domain…includes those objectives which deal with the recall or recognition of knowledge and the development of intellectual abilities and skills. This is the domain … in which most of the work in curriculum development has taken place and where the clearest definitions of objectives are to be found phrased as descriptions of student behavior.

A second part of the taxonomy is the affective domain. It includes objectives which describe changes in interest, attitudes and values and the development of appreciations and adequate adjustment." [1:7]

The cognitive taxonomy depicted a hierarchy of skills based on a vocabulary classifying levels of learning building from less to more sophisticated where, as noted in [6], "Within the cognitive domain, the six cognitive-learning levels are: knowledge, comprehension, application, analysis, synthesis and evaluation."

So, in addressing point 1 above: where professional skills such as "teamwork" did not easily fit within a cognitive taxonomy, they were not readily assessed and so rated at level 0 of the 'skills' taxonomy. In discussing more complex activities which might be evidenced through group work, Bloom made the following points.

It is probable that tasks involving synthesis objectives provide a wider kind of experience than those involving mainly acquisition of ideas. … pupils may work as a group defining important problems…proposing hypotheses to account for phenomena, planning simple experiments to test these ideas and actually carrying out the experiments either individually or in small groups. Such activities should foster productive thinking, some independence in approach as well as cooperativeness … Synthesis objectives occur at most levels of education. Obviously, the tasks corresponding to these objectives will differ in their magnitude and complexity from level to level. We would expect a progression from relatively small tasks to much larger tasks as the student moves through the educational program. [2:165–166]

So, we see that in defining "synthesis" as a cognitive level of learning involving larger tasks, the expected behaviours of students inherently include more socio-emotional dimensions. So, in linking competencies and larger tasks we require a to need arise for a partnership between both the cognitive and affective taxonomies. As an example of how the affective taxonomy may better express levels of achievement of a professional knowledge area, Lynch and colleagues have taken the professional outcome of "Teamwork" and mapped it to the five levels of the affective taxonomy [11]. This tabulation is given in Table 1.

A key distinction to be considered here as suggested by Lynch et al. [11] in going beyond the cognitive domain, is the notion of "internalization."

Krathwohl et al. _1964_ found a great diversity of imprecise affective terminology. Terms such as interest, appreciation, attitudes, and values are commonly used to cover portions of a large range of achievement—from simple awareness to the point of absorption into internal structures guiding behavior. In response, they settled on a single continuum, internalization, as an organizing principle; and were able to construct a hierarchy of five major levels along this continuum. … Progression from Level 1 to Level 5 denotes an increasing level of internalization of interests, attitudes, and/or values. [11]

This taxonomy then enables us to address the concerns raised by Johnny's first insight and map a professional knowledge area to one of five levels, rather than, with Johnny, having to resort to defining "teamwork" at a default level 0, based solely on its absence from the cognitive taxonomy of "skills."

For Johnny's second insight: in subsequently allocating dispositions, and distinguishing between the cognitively framed notion of skills and junior and senior developer expectations of the degree of exhibition of a disposition, it is clear that the allocation of skills fails to separate the level of a disposition from the adoption of the cognitive level of learning, which is primarily derived from the size and nature of the task chosen to frame the competency. However, the adoption of the affective taxonomy may provide a way to distinguish the depth of internalization of a disposition. The affective taxonomy's core notion of internalization here fits well with the concept of a disposition as "… a disposition "concerns not what abilities people have, but how people are disposed to use those abilities" [12].

In his analysis, Johnny applied the CC2020 competency model to a selected set of job advertisements, including tallying the knowledge areas as well as the professional knowledge areas, to profile the knowledge expectations. His more analytical findings are briefly reported in Table 2 (see next page.)

So, returning to Johnny's second insight, if we allocate skills from the cognitive taxonomy as outlined in Table 5 of the ITiCSE WG report [6] and based on the CC2020 Competency model [5] we need to do so at the overall level of competency as exhibited in the context of the task. But that fails to fully unpack the level of a specific chosen disposition, e.g., does being collaborative as a junior developer pose the same demands as being collaborative as a senior developer, although it is a disposition required in both roles at their differing levels of seniority?

While Lynch et al. [11] assert that:

"there is overlap of the cognitive and affective domains, especially at the lower levels of achievement…But beginning at affective Level 3 "valuing," we find the most obvious departure from cognitive categories and beyond Level 3, increasing affective achievement is uniquely described in terms not relevant in the cognitive domain.

In addition to overlap at lower levels of achievement, there is synergy among the two domains throughout all levels. Both domains may express concern about different aspects of the same thing. But clearly, knowledge about something is different than internalization of a value related to it and expressing that value in professional action."

Lynch et al. [11] represent the evolution of the process of internalization, through an "Example profile of BOK2 outcomes showing suggested affective levels of achievement through formal education" for a Body of Knowledge for Civil Engineering of selected professional outcomes. The professional outcome of Teamwork as tabulated in Table 1 above provides one example. The first three levels of: 1) Receiving, 2) Responding, 3) Valuing—are positioned at the undergraduate level of achievement. Level 4) Organizing/conceptualizing—is positioned at the Postgraduate level of achievement, and level 5) Characterizing by a value complex is deemed to apply at the senior professional level beyond the formal education stage of a professional engineer's career.

Thus, while the combination of cognitive and affective taxonomies discussed here is complex, they may provide a way in which to capture the complexity of competencies and the evolution of each of their discrete elements. So, while this is early work, perhaps we have a potential strategy for augmenting the CC2020 Competency Model and remain true to the goal of identifying competencies transcending knowledge-based curricula and encompassing the realities of learning combining both cognition and affect.

References

1. Anderson, L. Krathwohl, D. et al. 2001. A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives, (abridged edition 1 ed.). (New York: Pearson. 2001).

2. Bloom, B. S. and Krathwohl, D. R. Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. (New York: David McKay Co., Inc., 1956).

3. Krathwohl, D. R., Bloom, B. S. and Masia, B. B. Taxonomy of educational objectives, the classification of educational goals. Handbook II: affective domain. (New York: David McKay Co. Inc., 1956).

4. Bowers, D. S. Sabin, M. Raj, R. K. and Impagliazzo, J. Computing Competencies: Mapping CC2020 Dispositions to SFIA Responsibility Characteristics. In Proceedings of the IEEE Global Engineering Education Conference (EDUCON). (IEEE: 2022), 428–437.

5. Clear, A., Parrish, A., and CC2020 Task Force. Computing Curricula 2020 - CC2020 - Paradigms for Future Computing Curricula. (New York: ACM. 2020).

6. Clear, A., Clear, T., Vichare, A., Charles, T., Frezza, S., Gutica, M.,…Pitt, F. Designing Computer Science Competency Statements: A Process and Curriculum Model for the 21st Century. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. (New York: ACM, 2020). https://doi.org/https://doi.org/10.1145/3437800.3439208.

7. Clear, T. THINKING ISSUES: Is Agility a Disposition and Can it be Taught? ACM Inroads, 12,1 (2021), 13–14.

8. Frezza, S., Clear, T., and Clear, A. Unpacking Dispositions in the CC2020 Computing Curriculum Overview Report. In 50th ASEE/IEEE Frontiers in Education Conference. (Uppsala, Sweden: IEEE, 2020).

9. He, J. Skills Requirements from Junior Software Developer to Senior Developer. Master of Computer and Information Sciences Dissertation, Auckland University of Technology, Auckland, 2023.

10. Hoque, M. E. Three domains of learning: Cognitive, affective and psychomotor. The Journal of EFL Education and Research, 2, 2 (2016), 45–52.

11. Lynch, D. R., Russell, J. S., Evans, J. C., and Sutterer, K. G. Beyond the cognitive: The affective domain, values, and the achievement of the vision. Journal of professional issues in engineering education and practice, 135, 1 (2009), 47–56.

12. Schussler, D.L. Defining dispositions: Wading through murky waters. The Teacher Educator 41,4 (2006), 251–268.

Author

Tony Clear
School of Computing and Mathematical Sciences
Auckland University of Technology
Private Bag 92006
Auckland, 1142 New Zealand
[email protected]

Figures

Figure 1. Conceptual Structure of the CC2020 Competency Model [Ex. 5 Fig 4.1 p. 47]