“Experts and experienced teachers do not differ in the amount of knowledge [they possess] … Experts possess knowledge that is more integrated, in that they combine new subject matter content knowledge with prior knowledge; [they] can relate current lesson content to other subjects in the curriculum.”

The different subjects of Informatics and Computer Sciences are thought of and taught in exclusion. End-user computing is taught without real contents and problems, relying heavily on concepts which novices and end-users usually do not have.

“Expert teachers teach and are prepared for a greater store of algorithms that students might use when solving a particular problem.”

This characteristic of expert teachers plays a crucial role in guiding students when they develop intuitive expertise. Intuitive expertise is the knowledge which System 1 needs for making reliable fast decisions [25] . Expert teachers are able to teach how knowledge at mathability Level 4 can be transferred to Level 3.

“Both expert and experienced teachers perform better than novices … because their cognitive skills become automatic with extensive practice” (Chase & Simon, 1973; Chi et al., 1981 in [13] ), [25] .

“The difference, rather, is that experts develop automaticity so as to free working memory to deal with other more complex characteristics of the situation, whereas experienced non-experts do not optimise the opportunities gained from automaticity.”

Expert teachers are much effective in activating System 1 and System 2 in the right proportion and within the right time frame, which has great importance in effective problem solving, in lightening the load of working memory, and in our case, in reducing the number of erroneous and demanding documents.

“The expert teacher more often than the experienced teacher seeks further information, whereas experienced teachers focus more on directly available data…”

Typing data, presenting meaningless and/or low mathability formulas, l’art-pour-l’art formattings, etc., and the acceptance of low mathability materials are widely accepted.

“Experts are more adept at anticipating problems and then improvising. They tend to spend a greater proportion of their solution time trying to understand the problem to be solved as opposed to trying out different solutions.”

In this aspect, the difference between experts and the others in computer problem solving is that they prefer high mathability and TAEW based approaches, respectively.

“They [experts] are better able to filter relevant from irrelevant information, and are able to monitor, understand, and interpret events in more detail and with more insight than experienced teachers.”

This is the aspect mentioned in connection with the definition and description of functions, where irrelevant information is focused on.

“Expert teachers aim for more than achievement goals. They also aim to motivate their students to master rather than perform, they enhance students’ self-concept and self-efficacy about learning, they set appropriate challenging tasks, and they aim for both surface and deep outcomes”,

This statement is in complete accordance with the Meaning System Model [43] .

“Expert teachers are more likely to set challenging rather than “do your best” goals, they set challenging and not merely time consuming activities, they invite students to engage rather than copy.”

This high mathability approach was hardly found in the analyzed materials; they primarily expected copying and surface navigation from students.