Conclusioni?

And now? How to con­clu­de the cour­se after three mon­ths of rea­dings and discussions?

I sug­ge­st rea­ding two arti­cles, choo­se one:

•  Michael Lodi and Simone Martini. Computational thin­king, bet­ween Papert and Wing. Sci & Educ 30, 883–908 (2021).
• Paulo Blikstein and Sepi Hejazi Moghadam. Computing Education. Literature Review and Voices from the Field. The Cambridge Handbook of Computing Education Research, Chapter 3. (2019)

I will use the­se two arti­cles to launch a final, broad discussion:

• What were your moti­va­tions for taking this cour­se? Have they changed?
• If you were to beco­me com­pu­ter scien­ce tea­chers in any form, what would dri­ve you?
• This is a cour­se on tea­ching. The fir­st rule for good tea­ching is to reflect on tea­ching itself. Think about the tea­ching that took pla­ce in this cour­se with a cri­ti­cal mind­set. What would you have chan­ged? What did I get wrong? What would you have done dif­fe­ren­tly? How would you impro­ve the cour­se? “Think wild­ly” and pro­po­se new ideas, even the most absurd ones. (*)
• (For tho­se inte­re­sted) The cour­se ends here, but it doe­sn’t mean it has to end here. I am curious to hear your ideas for pos­si­ble col­la­bo­ra­tions bet­ween uni­ver­si­ties and schools. What does the school lack that the uni­ver­si­ty can pro­vi­de? How could col­la­bo­ra­tion bet­ween tea­chers (cur­rent and futu­re) be orga­ni­zed in the coming years?

(*) I know, I am the pro­fes­sor and I still have to give you a gra­de. But the fact that we have never tal­ked about eva­lua­tion speaks volu­mes about what I think about eva­lua­tion. Relax and feel free to cri­ti­ci­ze as you wish.