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--- work:semana_17_de_2022 [2022/04/27 21:48] – [Research] magsilva
+++ work:semana_17_de_2022 [2022/04/28 02:50] (current) – magsilva
@@ Line 9: / Line 9: @@
   * Skimmed through the latest issues of Journal of Computing Sciences in Colleges.
     * Read "Teaching data representation using real-world applications" and used it as inspiration to create the concept map on data representation. It was a nice touch that the paper used bit flippers (“Flippy Do", from Code.org) to teach binary encoding of decimal and fractional numbers, and the [[https://www.nytimes.com/2021/02/24/science/nasa-mars-parachute-code.html | Mars 2020 Lander parachute]] to teach encoding of textual data.
+    * While reading the previous paper, I stumbled on some papers about propositional logic: "InfoTraffic: teaching important concepts of computer science and math through real-world examples" (10.1145/1227504.1227349). It provides a nice online application to learn about propositional logic, using road traffic control as a metaphor: https://logictraffic.ch/.
+    * Read "An online tool for easy-to-set-up, visualizer-based, and auto-gradable full tracing exercises". It is well suited to program understanding and debugging competencies, as required in the Programming Fundamentals exam I applied to my students last Monday. The tool. TracingQuiz, builds upon PythonTutor's visualizer, requiring the student to answer a quiz for each line under execution. It should be available at https://tracingquiz.xyz/, but I couldn't access it (access denied).  After some digging, I found out [[https://sigcse.org/files/SpecialProjectReports/SP-report-2019-Jin.pdf | TrackingQuiz was a SIGCSE special project]] and it was actually available at https://tracing-quiz.herokuapp.com/. Unfortunately, although that website is available, there is no course available to join and it is not possible to create a new course.
+    * Finally, aligned with the recent curriculum design at [[BCC]], I read "Beyond big O: teaching experimental algorithmics". It addresses students' competencies regarding algorithm performance.