350227 UE BF1I - Training Processes - Abt. B (2023W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 04.09.2023 09:00 bis Mi 20.09.2023 12:00
- Anmeldung von Mo 02.10.2023 09:00 bis Fr 06.10.2023 12:00
- Abmeldung bis Di 31.10.2023 12:00
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Donnerstag 05.10. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 12.10. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 19.10. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 09.11. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 16.11. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 23.11. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 30.11. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 07.12. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 14.12. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 4. Stock
- Donnerstag 11.01. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 18.01. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
- Donnerstag 25.01. 13:30 - 15:00 ZSU - USZ II, Seminarraum II, 1. Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Partial achievements include:
- Active participation in face-to-face sessions.
- Analysis of two relevant articles in a Journal Club (9th session).
- Recapitulation and reflection on learned concepts during a Teachback Workshop (11th session).
- Delivering presentations and engaging in peer review with constructive feedback for fellow students (6th and 14th sessions).
- Submission of a written training process by the end of the semester.The use of AI is explicitly permitted in this course. AI can be employed for tasks such as revising and correcting self-authored texts or providing support in coding.Please note that any instance of academic misconduct (e.g., cheating, plagiarism, unauthorized use of aids, falsification, ghostwriting, etc.) will result in the entire course being considered dishonestly completed, and it will be counted as an attempt. (Entry in U:SPACE: X = not assessed).
- Active participation in face-to-face sessions.
- Analysis of two relevant articles in a Journal Club (9th session).
- Recapitulation and reflection on learned concepts during a Teachback Workshop (11th session).
- Delivering presentations and engaging in peer review with constructive feedback for fellow students (6th and 14th sessions).
- Submission of a written training process by the end of the semester.The use of AI is explicitly permitted in this course. AI can be employed for tasks such as revising and correcting self-authored texts or providing support in coding.Please note that any instance of academic misconduct (e.g., cheating, plagiarism, unauthorized use of aids, falsification, ghostwriting, etc.) will result in the entire course being considered dishonestly completed, and it will be counted as an attempt. (Entry in U:SPACE: X = not assessed).
Mindestanforderungen und Beurteilungsmaßstab
All partial achievements mentioned above must be completed within the communicated deadlines to receive a favorable assessment.Assessment Key:(1) 91 -100 points
(2) 81 - 90 points
(3) 71 - 80 points
(4) 60 - 70 points
(5) < 60 points
(2) 81 - 90 points
(3) 71 - 80 points
(4) 60 - 70 points
(5) < 60 points
Prüfungsstoff
Literatur
Zuordnung im Vorlesungsverzeichnis
BF1I
Letzte Änderung: Mi 22.11.2023 15:48
- Develop the competence to effectively plan, carry out, and critically evaluate training units in alignment with training science principles
- Skillfully design and coordinate load parameters within the contexts of training application and training control.
- Demonstrate proficiency in facilitating and incorporating both self-reflection and external feedback into the training process, including thorough documentation of training activities.Content:
- Tests and assessments
- Monitoring
- Data management systems
- Application of training science conceptsMethods:
- Seven units are structured as interactive lectures accompanied by group discussions, serving as the foundational knowledge for subsequent activities.
- Students are tasked with practical applications of course material, applying it to either a fictitious or real-world scenario. This hands-on approach will allow them to develop expertise in test planning, execution, and evaluation, as well as the critical aspects of training management, control, data analysis, and presentation.