The methodology combines guided, supervised, and autonomous activities. Students will take an active role.

Guided activities (25%)

Attendance and participation in lectures, lab practices, field trips, etc., and the completion and assessment of proposed activities.

Supervised activities (5%)

Completion, review, and evaluation of proposed tasks (reports, case studies, problem solving, presentations)

Autonomous activities (70%)

Analysis of readings and didactic innovation proposals, writing reports, designing activities, analyzing and solving cases.

Note: 15 minutes of one class will be reserved, within the schedule established by the institution/degree program, for students to complete surveys evaluating teaching performance and the course/module itself.

To pass this course, students must demonstrate strong general communication skills, both oral and written, and a good command of the Catalan language.

All tasks must be submitted within the established deadlines. If tasks are not submitted on time, an additional one-week period will be granted, but the maximum grade for each activity will be 5 out of 10.

Evaluation activity: mathematical modelling (30%): This task is carried out in small groups and must be submitted by mid-December.

Evaluation activity: analysis of teaching resources for mathematics education (20%): This task is carried out in pairs and must be submitted by the end of January.

Research Assessment Activity in the Secondary School Classroom - Research Question and Objectives (20%): This task is carried out individually and must be submitted before the start of the second teaching placement.

Research Assessment Activity in the Secondary School Classroom - Data Coding (30%): This task is carried out individually and must be submitted at the end of the course.

To pass the module, students must submit all evaluation activities and obtain a minimum grade of 5 out of 10 in each. If an activity is failed, students will have 10 working days to resubmit it, starting from the day the grade is communicated. If the activity on the design and implementation of rich classroom activities must be resubmitted, a 10-day period for in-person resubmission will be granted, starting from the end of the course.

Feedback on assignments and tests will be provided within 20 working days after submission and/or completion.

Plagiarism is considered a serious offense: if plagiarism is detected in an assignment, it will be invalidated, must be redone, and the maximum grade will be 5.

Correct and appropriate language use is essential in all submissions. Linguistic accuracy will be considered in the evaluation of all work.

A student will be graded as not assessable if they fail to submit assignments that account for more than one third of the final grade.

This course does not allow a synthesis exam in the case of a second enrollment.

For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for tasks authorized by the instructor. Students must clearly identify which parts were generated with this technology, specify the tools used, and include a critical reflection on how these influenced the process and the final result of the activity. Failure to disclose the use of AI in any assessable activity will be considered academic dishonesty and will result in a total penalty (zero) for that activity.

Single assessment

Students who opt for the single assessment must follow the course development, attending classes regularly under the same attendance conditions as students in continuous assessment. They will submit all evaluation activities individually on a single date at the end of the teaching period and must pass a validation test for each activity. The activities must be submitted during the last two weeks of the course’s teaching schedule.