Impact of SOLO Taxonomy in Computer Aided Instruction to Qualitative Outcome of Learning for Secondary School Children

A Comparative Study to Evaluate the Educational Impact of E-Learning Tools on Griffith University Pharmacy Students’ Level of Understanding Using Bloom’s and SOLO Taxonomies

“…To examine overall results, we averaged the total student performance (as measured by SOLO score) on all questions except the reference question and found that the students from the intervention group outperformed their peers, though the difference was not significant. Similar results were found by a study on secondary school children to evaluate the impact of e-learning tools on student level of understanding using SOLO taxonomy [33]. Another study for secondary school students found that e-learning tools helped students to proceed into higher level of understanding when compared with the traditional teaching method [37].…”

“…This taxonomy consists of five levels of increasing structural complexity: prestructural (students report unorganized and unstructured pieces of information), unistructural (students can use terminology, recite information, and identify names), multistructural (students are able to describe, classify, combine, and apply methods), relational (students understand relations between several aspects and how they might fit together to form a whole), and extended abstract (students may generalize structure beyond what was given, may perceive structure from many different perspectives, and transfer ideas to new areas) [32]. SOLO taxonomy has been used successfully by other researchers to measure cognitive learning outcomes and qualitatively evaluate student performance in different courses among different levels of students [25,[32][33][34]. Description of the scoring system is available in Table 1.…”

The application of artificial intelligence assistant to deep learning in teachers' teaching and students' learning processes

“…In this round of action research, there was no student in the experimental class in the pre-structured state of learning, while there were four students in the control class. This shows that students' state of learning was constantly improving and that teaching and learning under the intelligent in-class teaching model was more effective (Bhattacharyya et al, 2012 ; Shi et al, 2020 ).…”

“…Designing an innovative teaching model based on AI technology: Aiming at teachers, students, and machines as the primary subjects, we make full use of artificial intelligence hardware and software such as big data, the Internet, and cloud computing to design teaching strategies under AI technology, proposing a model covering pre-class, in-class, and after-class teaching, respectively. The teaching methods under this model can achieve precision and personalized teaching through human–machine integration and intelligent real-time interaction between teachers and students with discussion as follows (Essid et al, 2006 ; Bhattacharyya et al, 2012 ; Karvounidis et al, 2019 ; Ladias et al, 2019 , 2020 ; Shi et al, 2020 ).…”

“…SOLO illustrates the qualitative differences between student responses as it describes levels of understanding. It classifies outcomes in terms of their complexity, so that a judgment may be made on the quality of student responses to assessment tassifies understanding into five (5) levels (Essid et al, 2006 ; Bhattacharyya et al, 2012 ; Karvounidis et al, 2019 ; Ladias et al, 2020 ; Shi et al, 2020 ; Li et al, 2022 ):…”