Ghana is one of the few countries that introduced artificial intelligence (AI) into schools through a new national computing curriculum in 2021, even before the development and proliferation of generative AI technologies such as ChatGPT. This new computing curriculum differs from the previous one by including computing concepts such as programming, algorithms, robotics and artificial intelligence. Despite the early adoption of AI concepts in the computing curriculum, little research has been conducted to evaluate whether this curriculum is producing its desired results, especially on the topic of AI. In this blog post, I look at the AI curriculum for Ghana, using Bloom’s Taxonomy to frame the content and the approach taken.

A computing classroom in Ghana

Bloom’s taxonomy, developed by Benjamin Bloom and his collaborators in 1956, is  “a framework for classifying statements of what we expect or intend students to learn as a result of instruction”1. This framework has been used by generations of teachers in primary, secondary and tertiary educational institutions for their lesson planning and teaching. Due to its widespread use in education, researchers have revised it over the years to maintain its usefulness. One of the widely known revisions was developed by Anderson and Krathwohl in 20012. The revised taxonomy, a two-dimensional framework, consists of knowledge and cognitive processes. It provides a structure for classifying educational goals and objectives and is useful for assessing the emphasis on learning objectives and any missed educational opportunities. It could also help teachers to measure students’ understanding at different cognitive levels. 

Level Description
 RememberRetrieving relevant knowledge from long-term memory.
 UnderstandDetermining the meaning of instructional messages, including oral, written, and graphic communication.
 ApplyCarrying out or using a procedure in a given situation.
AnalyseBreaking material into its constituent parts and detecting how the parts relate to one another and to an overall structure or purpose.
EvaluateMaking judgments based on criteria and standards.
CreatePutting elements together to form a novel, coherent whole or make an original product.
Table 1: Descriptions of the levels of cognitive processes from Anderson and Krathwohl’s revised taxonomy

The computing curriculum for Junior High Schools (JHS) in Ghana (Year 8 – Year 10)

The JHS Computing Curriculum is organised into strands, sub-strands, content standards, indicators and exemplars3.

The curriculum has four strands from Basic 7 to Basic 9, namely: introduction to computing, productivity software, communication networks, and computational thinking. In Ghana, Basic 7 is equivalent to Grade 7 (Year 8 in England), Basic 8 to Grade 8 (Year 9 in England), and Basic 9 to Grade 9 (Year 10 in England).

Each strand is further divided into sub-strands. Figure 1 shows the strands and their respective sub-strands, with Figure 2 showing an example of the content.

Figure 1: A summary of the scope of the curriculum

Figure 2 is an example of what students are expected to know about AI in Basic 9.

Figure 2: A snapshot of what students are expected to know about AI in Basic 9

Applying Bloom’s Taxonomy to the Ghanaian AI curriculum

Here I will show how the revised taxonomy can be used to assess the cognitive expectations placed on students as they learn about AI by mapping the indicators for Basic 7 (B7), Basic 8 (B8), and Basic 9 (B9) in the curriculum to the cognitive levels as shown in Figure 3. 

Figure 3: The indicators of AI in the curriculum mapped onto Bloom’s taxonomy

The diagram shows that students are expected to analyse conceptual areas of AI, such as differentiating human and machine intelligence in B8. This is evident by the use of action words, such as “compare” and “discuss”. I also noticed that students have the opportunity to collect data and train a machine learning (ML) algorithm in a web-based tool. This has been classified under the “apply” level since students would have the opportunity to learn the different stages of ML models in a highly scaffolded manner. Learning both the conceptual and practical aspects of AI is important.

However, there are a few issues that teachers and stakeholders should be aware of while adhering to the indicators for AI within the curriculum. Teachers may not be aware of the need to guide students to evaluate data collection and data processing methods or to evaluate AI algorithms and their output as these are not explicitly stated in the curriculum. Students not having the right skills to evaluate data collection, preprocessing and model training stages of AI development could make them susceptible to algorithmic bias both in the present and future. Hence, these aspects of AI should be emphasised in schools. Additionally, using the lens of Bloom’s taxonomy, there is no indication in the curriculum that students are expected to create their own ML models to solve problems around them. We all know that being creative and improving our creativity is desirable. Therefore, my opinion is that it should be a priority for teachers and all stakeholders to support students in building their problem-solving and critical-thinking skills while they learn about concepts around AI in schools.

Teaching AI with the Ghanaian JHS curriculum

One way teachers can ensure that students acquire relevant AI competencies in secondary schools is to provide more emphasis on the  “apply”, “evaluate” and “create” levels of the revised Bloom’s taxonomy while they teach and assess students’ knowledge of AI. This is not an easy responsibility for teachers, especially knowing that they have no or little knowledge about AI. Some suggestions and resources to serve as a guide and support for teachers as they prepare to teach AI concepts in schools are as follows:

  1. Adapt resources, such as  Exploring computer science (AI unit) and Experience AI resources to support your teaching of data processing and machine learning concepts in B9.
  2. Develop teaching strategies that could help represent the subject matter of AI appropriately for students (For example: Top 10 Hands-On AI Activities for kids and the classroom (aiclub.world)).
  3. Learn more about how other teachers are approaching AI as a topic in school in the Hello World magazine by Raspberry Pi Foundation.
  4. Assess students’ understanding of AI or computing concepts by using the revised Bloom’s taxonomy as a guide. Aim for students to operate within the “apply”, “analyse” and “create” levels of the taxonomy.
  1. Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Handbook I: cognitive domain. New York: David McKay. ↩︎
  2. Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives: complete edition. Addison Wesley Longman, Inc. ↩︎
  3. National Council for Curriculum and Assessment (2021). Common Core Programme. ↩︎