Examples from…. Artificial Intelligence module This phase of the module has been developed in two activities. a) “
Examples from…. Artificial Intelligence module This phase of the module has been developed in six activities. The activities guide the students to grasp the paradigm shift in programming Artificial Intelligence that occurred with machine learning: unlike the traditional forms of programming, in machine learning a machine learns to solve a problem or to perform a task without knowing the strategy (an explicit knowledge base or the sequences of actions to be performed). It learns by “looking” at examples taken from appropriate databases. In order to reach these goals, a problem has been chosen – winning the TIC-TAC-TOE game – and students are guided to compare how the different programming approaches would address the problem. In particular, a set of six activities was designed: three activities (Activities 3-4-5) introduce three different approaches (imperative, logical-declarative, machine learning) and three activities (Activities 3bis – 4bis – 5bis) show how a computer can be programmed to play “TIC-TAC-TOE” following the various approaches. The examples are programs in typical language of each approach – respectively Python for imperative programming; Prolog for declarative programming; MATLAB for Machine Learning, but students do not need to know the languages. The activities are designed to stress the logics and not the technicalities. The six activities are designed to xxxxxx a circular dynamics to connect conceptual and epistemological knowledge and epistemic practices. In particular, their comparison should allow a teacher to stress: • the kind of structure of casual reasoning (linear or not) and of paradigm of prediction (deterministic or not) underpin each approach and what features characterize each form of reasoning; • the point of view of the complexity that characterises the approach based on examples with respect to the “classical” ones. Quantum Computing module This phase of the module has been developed in seven activities. In these activities, by studying different numeral systems, logical operations, algorithms and hardware components students prepare themselves to make the fundamental shift in computing paradigm and replace bits with qubits. Learning the quantum properties using the “spin first” approach paves the way for understanding quantum algorithms and thereby the superior computing power and future opportunities offered by quantum computers.
Examples from…. Artificial Intelligence module This phase of the module has been developed in two activities “Possible future scenarios: which values, which scientific, technological, social issues are involved in each of them? The activity guides students to turn the scientific concepts of prediction, projection, space of possibilities, scenarios (concepts developed in activities 1 -7-8) into skills to think of different ways to realize possible future scenarios. In order to reach this goal, three different scenarios for the town of Ada have been designed and students are led to analyse and discuss them. In particular, the students are guided to compare the values they embed, to think about their preferences and idiosyncrasies and to think about the possible events, related to different citizenship decision or plans that may have caused them. “Desirable future, back-casting and action planning: what actions and what action competence can contribute to realize the desirable future?” The first part of the activity is closely related to the above activity and guide the students to image their desirable future, where they wish to live.
Examples from…. Artificial Intelligence module “Desirable future, back-casting and action planning: what actions and what action competence can contribute to realize the desirable future?” The activity is focused on the concept of desirable scenarios and, through action competence strategies, the students are guided to play with forecasting and back-casting dynamic between present and future. The students are guided to work in groups and to plan actions that can contribute to realizing their desirable scenario and to solve, with an original idea, a pressing issue of today. This is the last activity of the module and, at the end, the students have to present their success story in the form of back-casting activity.
Examples from… the Collections The following shots show some examples from the different collections. Unfortunately some images are missing from Europeana Cloud, e.g. 31% from BE-MRAC All thumbnails of BE-CAG. Therefore we use image URLs pointing to NTUA MINT, e.g. xxxx://xxxxxxxxxxxx.xxxxx.xxxx.xx/image/CAG/00009803_1.JPG instead of xxxxx://xxxxx.xxxxxxxxx.xx/api/data- providers/CAG/records/00009803_1.JPG/representations/presentation/CAG/0 0009803_1.JPG Figure 1 BG-ONTO: Bulgarian Recipes Figure 2 IT-ALI: Old Photos Figure 3 UK-HM: Ethnographic Collection Figure 4 BE-MRAC: Ethnographic Collection, Old Photos Figure 5 BE-CAG: Mostly Modern Food-related Artefacts Figure 6 UK-HP: London Pubs Figure 7 IE-LGMA: Irish Plants and Foods Figure 8 UK-TOP: Mix of Old Photos and Modern Food & Drink Photos Figure 9 UK-CT: Victoria & Xxxxxx Food-related Artefacts Figure 10 LT-VUFC: Old Lithuanian Recipes
