Model STEM module: 2 semester 20 credit

Based on a Level 1 UG Engineering fundamentals module that fits within an existing programme structure
Notes: 
- Based on cohort of ~150-200 students 
- Jan exam period used for teaching as no ‘formal’ exams on current programme
- Module includes Computer Labs
Model STEM module: 2 semester 20 credit
Based on SCALA (Student-centred active learning approach)
Notes on Assessment
-
The Assessment has been changed to increase the weighing to in-session assessments
-
The submissions are all online via Gradescope
Caution:
There are wide range of other module formats in EPS
(e.g. Design based, Studio based, Lab based)
This example may not be a suitable template for these!
These 6 Topics to be highlighted on timeline
info-graphic graphic (see next slide)
Assessment timeline included in Assessments
Asynchronous (directed activities)
Synchronous (live activities)
(some ‘live’ interaction each week)
Online activity
Face-2-face (F2F)
Virtual computer lab
Short online task/quiz 
–auto feedback 
(e.g. tophat, MCQ, Mobius etc)
Pre-quiz 
(check knowledge (e.g. Tophat)
Group Example class 
(50min)
Summative submission
(all via Gradescope)
Discussion area for module – possibly in TEAMs or Padlett or similar
Assessments (set and submission)
<25min screencast (or similar)
Group session run
multiple times
Live interactive session in CU
(full cohort)  (1xhour): (
either examples / scene
setting/Q&A uses interaction chat/polling/Tophat)
Minerva
pages
available
Message
to
students
Assessment set
Computer Lab 
(~2 hour)
Other formative activity
(e.g. prework for workshop/computer lab
Topic1: xxxxx  (Dr X)
Topic 2: xxxxx (Prof Y)
Topic3: xxxxx (Dr X)
Formative task
Students encouraged to meet F2F (socially distanced) as small groups to complete example/ pre-work activities (e.g. in their tutor groups)
Learning Outcomes
(O1) develop knowledge and 
understanding of ‘subject XXXX 
and understanding of the principles of general XXXX;
(O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to 
apply quantitative methods and computational tools (e.g. Matlab, Excel, Python)
;
(O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX 
 of their assumptions and limitations
;
(O4) be able to 
construct simple mathematical models 
from real problems and have the ability to assess model limitations;
(O5) be able to model problems related to XXXX and develop experience at using 
computational tools
 to solve XXXX;
Example 
(Eng101:  20 credit UG level1 ‘fundamentals’ module, running over both semesters) 
SEMESTER 1
 
Live interactive session
(30min)  Q&A, feedback
or
Delivery type
Delivery type
Assessment types
Discussion area for module – possibly in TEAMs or Padlett
Minerva page
available
Message to
students
Topic 4: xxxx (Prof Y)
Topic 5: xxxxxx (D
r xxxx)
Option 
A
 -F2F (with full return campus)
Topic 6:
xxxxxxx
Revision sessions
Asynchronous (directed activities)
Synchronous (live activities)
Assessments (set and submission)
Students encouraged to meet F2F as small groups to share ideas
Online activity
Face-2-face (F2F)
Virtual computer lab
Short online task/quiz 
–auto feedback 
(e.g. tophat, MCQ, Mobius etc)
Pre-quiz 
(check knowledge (e.g. Tophat)
Group Example class 
(50min)
Summative submission
(all via Gradescope)
<25min screencast (or similar)
Group session run
multiple times
Live interactive session in CU
(full cohort)  (1xhour): (
either examples / scene
setting/Q&A uses interaction chat/polling/Tophat)
Assessment set
Computer Lab 
(~2 hour)
Other formative activity
(e.g. prework for workshop/computer lab
Live interactive session
(30min)  Q&A, feedback
or
Delivery type
Delivery type
Assessment types
Example 
(Eng101:  20 credit UG level1 ‘fundamentals’ module, running over both semesters) 
SEMESTER 2
 
Week 13
Week 14
Learning Outcomes
(O1) develop knowledge and 
understanding of ‘subject XXXX 
and understanding of the principles of general XXXX;
(O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to 
apply quantitative methods and computational tools (e.g. Matlab, Excel, Python)
;
(O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX 
 of their assumptions and limitations
;
(O4) be able to 
construct simple mathematical models 
from real problems and have the ability to assess model limitations;
(O5) be able to model problems related to XXXX and develop experience at using 
computational tools
 to solve XXXX;
Easter break (out of term)
(no formal exams)
Exam period
Revision
week
Week 18
Week 19
Week 20
Week 21
Week 22
A
Programme level
Fieldtrip/Lab weeks
Discussion area for module – possibly in TEAMs or Padlett
Minerva page
available
Message to
students
Topic 4: xxxx (Prof Y)
Topic 5: xxxxxx (D
r xxxx)
Option 
B
 limited F2F 
Topic 6:
xxxxxxx
Revision sessions
Asynchronous (directed activities)
Synchronous (live activities)
Assessments (set and submission)
Online activity
Face-2-face (F2F)
Virtual computer lab
Short online task/quiz 
–auto feedback 
(e.g. tophat, MCQ, Mobius etc)
Pre-quiz 
(check knowledge (e.g. Tophat)
Group Example class 
(50min)
Summative submission
(all via Gradescope)
<25min screencast (or similar)
Group session run
multiple times
Live interactive session in CU
(full cohort)  (1xhour): (
either examples / scene
setting/Q&A uses interaction chat/polling/Tophat)
Assessment set
Computer Lab 
(~2 hour)
Other formative activity
(e.g. prework for workshop/computer lab
Live interactive session
(30min)  Q&A, feedback
or
Delivery type
Delivery type
Assessment types
Example 
(Eng101:  20 credit UG level1 ‘fundamentals’ module, running over both semesters) 
SEMESTER 2
 
Week 13
Week 14
Learning Outcomes
(O1) develop knowledge and 
understanding of ‘subject XXXX 
and understanding of the principles of general XXXX;
(O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to 
apply quantitative methods and computational tools (e.g. Matlab, Excel, Python)
;
(O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX 
 of their assumptions and limitations
;
(O4) be able to 
construct simple mathematical models 
from real problems and have the ability to assess model limitations;
(O5) be able to model problems related to XXXX and develop experience at using 
computational tools
 to solve XXXX;
Easter break (out of term)
(no formal exams)
Exam period
Revision
week
Week 18
Week 19
Week 20
Week 21
Week 22
B
Programme level
Fieldtrip/Lab weeks
Students encouraged to meet F2F (socially distanced) as small groups to complete example/ pre-work activities (e.g. in their tutor groups)
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Within an existing programme structure, a Level 1 UG Engineering fundamentals module designed for a cohort of ~150-200 students. Assessment weighting shifted towards in-session assessments with online submissions. Utilizes SCALA approach for student-centered active learning. Incorporates computer labs and emphasizes practical, hands-on learning experiences.

  • STEM
  • Engineering
  • Active Learning
  • Assessment
  • Student-Centered

Uploaded on Feb 16, 2025 | 0 Views


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  1. Model STEM module: 2 semester 20 credit Based on a Level 1 UG Engineering fundamentals module that fits within an existing programme structure Notes: - Based on cohort of ~150-200 students - Jan exam period used for teaching as no formal exams on current programme - Module includes Computer Labs Notes on Assessment - - The Assessment has been changed to increase the weighing to in-session assessments The submissions are all online via Gradescope Caution: There are wide range of other module formats in EPS (e.g. Design based, Studio based, Lab based) This example may not be a suitable template for these! Based on SCALA (Student-centred active learning approach)

  2. To be updated to give fuller picture of module delivery and timings. This could include a info-graphic to show the learning journey These 6 Topics to be highlighted on timeline info-graphic graphic (see next slide) Assessment timeline included in Assessments

  3. Example (Eng101: 20 credit UG level1 fundamentals module, running over both semesters) SEMESTER 1 Induction week Week 11 Week 2 Week 3 Week 1 Delivery type Delivery type Assessment types Group session run multiple times Short online task/quiz auto feedback (e.g. tophat, MCQ, Mobius etc) Live interactive session in CU (full cohort) (1xhour): (either examples / scene setting/Q&A uses interaction chat/polling/Tophat) or Online activity Assessment set Pre-quiz (check knowledge (e.g. Tophat) Face-2-face (F2F) Computer Lab (~2 hour) Live interactive session (30min) Q&A, feedback Summative submission (all via Gradescope) Virtual computer lab Other formative activity (e.g. prework for workshop/computer lab Group Example class (50min) <25min screencast (or similar) Asynchronous (directed activities) Message Minerva students available pages to Synchronous (live activities) (some live interaction each week) Assessments (set and submission) Formative task Discussion area for module possibly in TEAMs or Padlett or similar Students encouraged to meet F2F (socially distanced) as small groups to complete example/ pre-work activities (e.g. in their tutor groups) Topic1: xxxxx (Dr X) Topic 2: xxxxx (Prof Y) Topic3: xxxxx (Dr X) ~O1 [5%] Gradescope HW ~O3,~O4,~O5 [10%] Gradescope HW ~O2, O3 Learning Outcomes Learning Outcomes (O1) develop knowledge and understanding of subject XXXX and understanding of the principles of general XXXX; (O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to apply quantitative methods and computational tools (e.g. Matlab, Excel, Python); (O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX of their assumptions and limitations; (O4) be able to construct simple mathematical models from real problems and have the ability to assess model limitations; (O5) be able to model problems related to XXXX and develop experience at using computational tools to solve XXXX;

  4. Option A -F2F (with full return campus) Example (Eng101: 20 credit UG level1 fundamentals module, running over both semesters) SEMESTER 2 Programme level Fieldtrip/Lab weeks Exam period Week 12 (no formal exams) Week 21 Week 22 Week 13 Week 14 Week 19 Week 20 Easter break (out of term) Revision week Week 18 Delivery type Delivery type Assessment types Group session run multiple times Short online task/quiz auto feedback (e.g. tophat, MCQ, Mobius etc) Live interactive session in CU (full cohort) (1xhour): (either examples / scene setting/Q&A uses interaction chat/polling/Tophat) or Online activity Assessment set Pre-quiz (check knowledge (e.g. Tophat) Face-2-face (F2F) Computer Lab (~2 hour) Live interactive session (30min) Q&A, feedback Summative submission (all via Gradescope) Virtual computer lab Other formative activity (e.g. prework for workshop/computer lab Group Example class (50min) <25min screencast (or similar) Minerva page Asynchronous (directed activities) Message to students available Synchronous (live activities) Assessments (set and submission) Discussion area for module possibly in TEAMs or Padlett Students encouraged to meet F2F as small groups to share ideas Topic 6: xxxxxxx Topic 5: xxxxxx (Dr xxxx) Topic 4: xxxx (Prof Y) Revision sessions O1, O3, O4 [70%] 48hr takehome exam ~O2, O5 [5%] Gradescope HW ~O2, O5 [5%] Gradescope HW ~O1, ~O2 [5%] Gradescope HW Learning Outcomes Learning Outcomes (O1) develop knowledge and understanding of subject XXXX and understanding of the principles of general XXXX; (O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to apply quantitative methods and computational tools (e.g. Matlab, Excel, Python); (O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX of their assumptions and limitations; (O4) be able to construct simple mathematical models from real problems and have the ability to assess model limitations; (O5) be able to model problems related to XXXX and develop experience at using computational tools to solve XXXX; A

  5. Option B limited F2F Example (Eng101: 20 credit UG level1 fundamentals module, running over both semesters) SEMESTER 2 Programme level Fieldtrip/Lab weeks Exam period Week 12 (no formal exams) Week 21 Week 22 Week 13 Week 14 Week 19 Week 20 Easter break (out of term) Revision week Week 18 Delivery type Delivery type Assessment types Group session run multiple times Short online task/quiz auto feedback (e.g. tophat, MCQ, Mobius etc) Live interactive session in CU (full cohort) (1xhour): (either examples / scene setting/Q&A uses interaction chat/polling/Tophat) or Online activity Assessment set Pre-quiz (check knowledge (e.g. Tophat) Face-2-face (F2F) Computer Lab (~2 hour) Live interactive session (30min) Q&A, feedback Summative submission (all via Gradescope) Virtual computer lab Other formative activity (e.g. prework for workshop/computer lab Group Example class (50min) <25min screencast (or similar) Minerva page Asynchronous (directed activities) Message to students available Synchronous (live activities) Assessments (set and submission) Discussion area for module possibly in TEAMs or Padlett Students encouraged to meet F2F (socially distanced) as small groups to complete example/ pre-work activities (e.g. in their tutor groups) Topic 6: xxxxxxx Topic 5: xxxxxx (Dr xxxx) Topic 4: xxxx (Prof Y) Revision sessions O1, O3, O4 [70%] 48hr takehome exam ~O2, O5 [5%] Gradescope HW ~O2, O5 [5%] Gradescope HW ~O1, ~O2 [5%] Gradescope HW Learning Outcomes Learning Outcomes (O1) develop knowledge and understanding of subject XXXX and understanding of the principles of general XXXX; (O2) apply XXXX methods, tools and notations proficiently in the analysis and solution of engineering problems with an ability to apply quantitative methods and computational tools (e.g. Matlab, Excel, Python); (O3) appreciate physical situations where these XXXX techniques are useful and develop knowledge and XXXX of their assumptions and limitations; (O4) be able to construct simple mathematical models from real problems and have the ability to assess model limitations; (O5) be able to model problems related to XXXX and develop experience at using computational tools to solve XXXX; B

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