## 5 Results of the Survey
### Results Related to AI  
Table 4 contains the answers to the question about disciplines used in teaching AI. The most used disciplines are computer science, mathematics and logic, while the philosophy of mind and linguistics are the least used disciplines. Table 5 presents information about areas of AI that are taught by academics. The most commonly taught areas are machine learning, deep learning, data mining, and computational intelligence, while the least common are cognitive computing, natural language processing, and computer vision. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**To What Extent Do You** & & & & & & & **To a Great** & **To a Very** & \\
**Tachel the Following** & **Not at All** & **To a Small** & **To Some** & **Kact** & **Moderate** & **Extent** & **Extent** & **No Answer** \\
**GAT** & & & & & & & & **Recent** \\ \hline Philosophy of mind & **44.9\%** & 30.4\% & 13.0\% & 5.8\% & 1.4\% & 0.0\% & 4.3\% \\ Cognitive modeling & **31.9\%** & **31.9\%** & 20.3\% & 2.9\% & 7.2\% & 1.4\% & 4.3\% \\ Mathematics & 14.5\% & 14.5\% & **26.1\%** & 21.7\% & 10.1\% & 11.6\% & 1.4\% \\ Logic & 8.7\% & **31.9\%** & 20.3\% & 15.9\% & 10.1\% & 8.7\% & 4.3\% \\ Linguistics & **37.7\%** & 30.4\% & 8.7\% & 11.6\% & 2.9\% & 1.4\% & 7.2\% \\ Computer science & 4.3\% & 8.7\% & 7.2\% & 10.1\% & **34.8\%** & **34.8\%** & 0.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Disciplines of AI in teaching, 100% = 69. Figure 6: Percent of academics teaching AI, IoT, and EC (86 answers in total). Figure 7: Academics’ teaching experience (86 answers in total). Table 6 shows answers to the question about teaching machine learning techniques used in artificial intelligence. Supervised and unsupervised learning techniques are taught at most, while reinforcement learning and semi-supervised learning are not popular. Information about teaching deep learning models is presented in Table 7. Collected data show that models contained in the question are not taught often. The most popular is the convolution neural network which has 40% answers pointing out a small contribution in teaching. This characteristic is even higher on the other models, omitted from the teaching process of 45% up to 67% of academics. Answers may indicate that academics are teaching other models than those presented in the questionnaire. Table 8 presents answers to the question about teaching the phases of the data mining process. Business understanding and deployment are skipped in the teaching process as arises from the answers. The first mentioned phases are related to general business management, while data mining is more bound to computer science. Academics who come from IT disciplines may not be management experts. Deployment of data mining solutions in a business requires conducting specific R&D work, which may be why this topic is not popular in teaching. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**To What Extent Do You** & & & & & & & \\
**Teach the Basic Machine Learning Techniques?** & & & & & & & \\ \hline Supervised learning & 8.7\% & 8.7\% & 8.7\% & 20.3\% & 21.7\% & **31.9\%** & 0.0\% \\ Semi-supervised learning & **27.5\%** & 21.7\% & 11.6\% & 17.4\% & 10.1\% & 8.7\% & 2.9\% \\ Unsupervised learning & 8.7\% & 21.7\% & 10.1\% & 17.4\% & **23.2\%** & 17.4\% & 1.4\% \\ Reinforcement learning & 26.1\% & **30.4\%** & 10.1\% & 17.4\% & 7.2\% & 5.8\% & 2.9\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Basic Machine Learning techniques in teaching, 100% = 69.