| Week | Date | Weekly Module | Discussion Type |
|---|---|---|---|
| 1 | Thu Aug 31 | W1: Getting started | Prof |
| 2 | Tue Sep 05 | W2: Intelligence 101 | Prof |
| 2 | Thu Sep 07 | W2 continued… | Prof |
| 3 | Tue Sep 12 | W3: Statistical Learning | Group |
| 3 | Thu Sep 14 | W3 continued… | Solo |
| 3 | Sun Sep 17 | Project Milestone #1 (Project Selection) Due | |
| 4 | Tue Sep 19 | W4: Statistical learning & other minds | Group |
| 4 | Thu Sep 21 | W4 continued… | Solo |
| 5 | Tue Sep 26 | W5: Modeling language | Prof |
| 5 | Thu Sep 28 | W5 continued… | Solo |
| 5 | Sun Oct 01 | Project Milestone #2 (Aspect of Intelligence) Due | |
| 6 | Tue Oct 03 | W6: Biases and origins | Group |
| 6 | Thu Oct 05 | Project Discussion | Solo |
| 7 | Tue Oct 10 | Fall Break!! NO CLASS | |
| 7 | Thu Oct 12 | W7: Perceptual Learning | Solo |
| 8 | Tue Oct 17 | W8: Modeling perception | Group |
| 8 | Thu Oct 19 | W8 continued | Solo |
| 8 | Sun Oct 22 | Project Milestone #3 (QALMRI/SPARK) Due | |
| 9 | Tue Oct 24 | W9: Emotional learning | Solo |
| 9 | Thu Oct 26 | W9 continued… | Solo |
| 10 | Tue Oct 31 | W10: Theory of Mind | Solo |
| 10 | Thu Nov 02 | W10 continued… | Solo |
| 10 | Sun Nov 05 | Project Milestone #4 (Project Plan) Due | |
| 11 | Tue Nov 07 | W11: Animal & Machine Theory of Mind | Group |
| 11 | Thu Nov 09 | W11 continued… | Prof |
| 12 | Tue Nov 14 | W12: Consciousness & sentience | Group |
| 12 | Thu Nov 16 | Psychonomics Conference: NO CLASS | |
| 13 | Tue Nov 21 | W13: Learning and Teaching | Solo |
| 13 | Thu Nov 23 | THANKSGIVING BREAK!!! NO CLASS | |
| 14 | Tue Nov 28 | W14: Culture and Conventions | Prof |
| 14 | Thu Nov 30 | W14 continued… | Solo |
| 14 | Sun Dec 03 | Project Milestone #5 (First Draft) Due | |
| 15 | Tue Dec 05 | W15: Human Uniqueness | Solo |
| 15 | Thu Dec 07 | Wrap! | Prof |
| 16 | Sun Dec 17 | Project Milestone #6 (Final Project) Due |
Syllabus
Intelligent Minds and Machines (PSYC 3043)
Welcome! This page hosts the syllabus for PSYC 3043.
Basic Course Information
Course number: PSYC 3043
Semester: Fall 2023
When: Tuesdays & Thursdays, 1:15 PM - 2:40 PM
Where: Adams 103
Website: You are here!
Pre-requisites: Three of:
- Either PSYC 2040 or PSYC 2060 (same as NEUR 2060)
- PSYC 2510
- PSYC 2520
Who is your instructor?
Abhilasha Kumar: Hear my name!
Pronouns: she/her
About me: I am a cognitive scientist who is fascinated by how humans think, learn, and communicate. My work involves conducting psychological experiments to understand different aspects of human behavior such as how we learn the meaning of words, how we search for information, and how we cooperate with one another. When I am not working, I enjoy playing board games, learning new recipes, and playing tennis (badly)!
Email: a.kumar@bowdoin.edu
Office: Kanbar Hall, Room 217
Student/Office Hours
- Tuesdays, 9-10 am
- Thursdays, 9-10 am
- Thursdays, 4-5.30 pm
- Fridays, 10-11 am
You are strongly encouraged to drop-in during student/office hours - this is time specifically dedicated to you and any thoughts, questions, or concerns you may wish to share with me. If the designated hours don’t work for you, please email me to find a different time.
What is this course about?
Why are humans considered the most “intelligent” species on the planet? Are there other minds around us that display intelligent behavior? Where does artificial intelligence (AI) fall short in mimicking intelligent behavior? This seminar course delves into several such fundamental questions about human cognition/intelligence and how our species is similar to and different from other minds and machines. We will discuss classic and modern approaches to understanding the mind, critically analyze various examples of intelligent behavior (such as language, perception, cooperation, sentience, etc.), evaluate recent work in machine learning and AI, and also draw insights about intelligence from the exciting literature on comparative (animal) cognition. You will read empirical articles, listen to podcasts, lead discussions, and also participate through spoken presentations and short writing assignments.
Why take this course? a.k.a. learning goals
The last few years have seen impressive highs and lows in the study and pursuit of intelligence. Through this course, I hope to communicate some of the excitement and skepticism that researchers in the field feel today. At the end of this course, you will be able to:
- Analyze and evaluate current approaches to defining, understanding, and building intelligence [Department Goal #4]
- Synthesize literature on a focused aspect of intelligence and produce an original critique [Department Goal #7]
- Develop an appreciation for cultural and ethical issues and perspectives surrounding the study of intelligence [Department Goal #3]
Course materials
All of the course materials will be available in a timely fashion on this course website and/or posted on Canvas.
Students do not need to purchase or download any textbook - all readings will be made available (or are already available) on this course website or on Canvas
Course structure
There are 15 total weeks in this course. Weekly learning modules will cover different subtopics in the study of intelligence under the umbrella of three core themes (language, perception, and complex cognition). Students will lead 2 discussions during the semester (1 solo and 1 paired) and are also expected to complete weekly assignments and a final project. All assignments provide opportunities to earn up to 100 points (+5 extra credit) toward a final grade.
This is an in-person class, and students are expected to attend all class sessions.
Working with difficult content
This course will briefly touch upon the history and practice of psychology and cognition. In doing so, we will cover some problematic and disturbing parts of history, including the Eugenics movement, the Holocaust, and their connection to intelligence testing and racism. These themes may also be revisited at later points in the course. You may find this content sexist, racist, homophobic, and/or otherwise unpleasant. Please know that our goal is not to endorse these attitudes but in fact acknowledge the part psychology has played in perpetuating these exclusionary ideologies throughout history. I understand, however, that some of this content may be difficult and upsetting. To that end, there are multiple ways to engage with the content via different types of assignments. I encourage you to push yourself, but also respect your limits and boundaries. If you are aware of any particular course material that may be traumatizing to you, please come talk to me and we can discuss alternative options for you to engage with the material. I will try my best to provide verbal reminders about such content ahead of time so that you are prepared and feel comfortable reaching out.
Weekly module structure
Weekly learning modules include three components to encourage engagement with the domain of intelligence in different ways.
READ: Modules have assigned readings from primary research articles or textbook chapters, and occasional podcast episodes. All material is freely available and posted on Canvas or the course website. Student are expected to read assigned material before classes where the material is discussed.
ANNOTATE: Students are expected to submit annotations for the class readings before each class. These annotations will serve as the jumping-off point for class discussions every week (see more details about annotations here)
REFLECT: Modules usually involve two class meetings. Classes will involve a mixture of student and instructor-led discussions, group work, and activities and students are expected to actively participate in class. At the end of the week, students are expected to choose and summarize ONE article/podcast from the assigned material using a fixed format (QALMRI or SPARK, see here).
Course Schedule
Assigned Materials
Week 1: Getting Started
Thursday, August 31, 2023: Prof
- Syllabus
- QALMRI + SPARK
Week 2: Intelligence 101
Tuesday, September 5, 2023: Prof
- Guests: Dr. Jen Coane and Dr. Sharda Umanath
- [SPARK] Yakushko, O. (2019). Eugenics and its evolution in the history of western psychology: A critical archival review. Psychotherapy and Politics International, 17(2), e1495.
- [QALMRI] Coane, J. H., Cipollini, J., Barrett, T. E., Kavaler, J., & Umanath, S. (2023). Lay Definitions of Intelligence, Knowledge, and Memory: Inter-and Independence of Constructs. Journal of Intelligence, 11(5), 84.
Thursday, September 7, 2023: Prof
- [QALMRI]Bian, L., Leslie, S. J., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science, 355(6323), 389-391.
- [SPARK] Griffiths, T. L. (2020). Understanding human intelligence through human limitations. Trends in Cognitive Sciences, 24(11), 873-883.
Week 3: Statistical Learning
Tuesday, September 12, 2023: Group
- [QALMRI] Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274(5294), 1926-1928.
- [SPARK] Saffran, J. R., & Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69, 181-203.
Thursday, September 14, 2023: Solo
- [QALMRI] Unger, L., Vales, C., & Fisher, A. V. (2020). The role of co‐occurrence statistics in developing semantic knowledge. Cognitive Science, 44(9), e12894.
Sunday, September 17, 2023
- Project Milestone #1 (Project Selection) due!
Week 4: Statistical Learning & Other Minds
Tuesday, September 19, 2023: Group
- [QALMRI] Hauser, M. D., Newport, E. L., & Aslin, R. N. (2001). Segmentation of the speech stream in a non-human primate: Statistical learning in cotton-top tamarins. Cognition, 78(3), B53-B64.
- [SPARK] Santolin, C., & Saffran, J. R. (2018). Constraints on statistical learning across species. Trends in Cognitive Sciences, 22(1), 52-63.
Thursday, September 21, 2023: Solo
- [SPARK] Turing, A. M. (1950). Computing Machine and Intelligence. MIND ,LIX, 433-460.
Week 5: Modeling Language
Tuesday, September 26, 2023: Prof
- [SPARK] Lake, B. M., & Murphy, G. L. (2021). Word meaning in minds and machines. Psychological Review.(27 Pages)
Thursday, September 28, 2023: Solo
- [QALMRI]Chen, D., Peterson, J. C., & Griffiths, T. L. (2017). Evaluating vector-space models of analogy. arXiv preprint arXiv:1705.04416. In Proceedings of the 39th Annual Conference of the Cognitive Science Society
- [SPARK] DeepMind Podcast: Speaking of intelligence(38 mins)
Sunday, October 1, 2023
- Project Milestone #2 (Aspect of Intelligence) due!
Week 6: Biases and Origins
Tuesday, October 3, 2023: Group
- [QALMRI] Garg, N., Schiebinger, L., Jurafsky, D., & Zou, J. (2018). Word embeddings quantify 100 years of gender and ethnic stereotypes. Proceedings of the National Academy of Sciences, 115(16), E3635-E3644.
- [SPARK]Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the dangers of stochastic parrots: Can language models be too big?🦜. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623).
Thursday, October 5, 2023: Solo
- [SPARK] Many Minds Podcast: What is language for? (1 h 17 mins)
- Project Discussion
Week 7: Perceptual Learning
Tuesday, October 10, 2023
- FALL BREAK! No class!
Thursday, October 12, 2023: Solo
- [QALMRI] Clerkin, E. M., Hart, E., Rehg, J. M., Yu, C., & Smith, L. B. (2017). Real-world visual statistics and infants’ first-learned object names. Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1711), 20160055.
- [SPARK]Smith, L. B., Jayaraman, S., Clerkin, E., & Yu, C. (2018). The developing infant creates a curriculum for statistical learning. Trends in Cognitive Sciences, 22(4), 325-336.
Week 8: Modeling Perception
Tuesday, October 17, 2023: Group
- [SPARK]LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
- [SPARK]DeepMind Podcast: Let’s get physical (33 mins)
Thursday, October 19, 2023: Solo
- [SPARK] Wichmann, F. A., & Geirhos, R. (2023). Are Deep Neural Networks Adequate Behavioral Models of Human Visual Perception?. Annual Review of Vision Science, 9.
Sunday, October 22, 2023
- Project Milestone #3 (QALMRI/SPARK) due!
Week 9: Emotional Learning
Tuesday, October 24, 2023: Solo
- [QALMRI] Plate, R. C., Wood, A., Woodard, K., & Pollak, S. D. (2019). Probabilistic learning of emotion categories. Journal of Experimental Psychology: General, 148(10), 1814.
- [SPARK]Ferretti, V., & Papaleo, F. (2019). Understanding others: emotion recognition in humans and other animals. Genes, Brain and Behavior, 18(1), e12544.
Thursday, October 26, 2023: Solo
- [SPARK]Picard, R. W. (2008). Toward machines with emotional intelligence. https://hdl.handle.net/1721.1/137903.2
Week 10: Theory of Mind
Tuesday, October 31, 2023: Solo
[QALMRI] Jara-Ettinger, J., Gweon, H., Tenenbaum, J. B., & Schulz, L. E. (2015). Children’s understanding of the costs and rewards underlying rational action. Cognition, 140, 14-23.
[QALMRI] Keysar, B., Lin, S., & Barr, D. J. (2003). Limits on theory of mind use in adults. Cognition, 89(1), 25-41.
Thursday, November 2, 2023: Solo
[QALMRI] Hawkins, R. X., & Goodman, N. D. (2016). Conversational expectations account for apparent limits on theory of mind use. In CogSci.
[SPARK] Shafto, P., Goodman, N. D., & Frank, M. C. (2012). Learning from others: The consequences of psychological reasoning for human learning. Perspectives on Psychological Science, 7(4), 341-351.
Sunday, November 5, 2023
- Project Milestone #4 (Project Plan) due!
Week 11: Animal and Machine Theory of Mind
Tuesday, November 7, 2023: Group
- [QALMRI] Buttelmann, D., Buttelmann, F., Carpenter, M., Call, J., & Tomasello, M. (2017). Great apes distinguish true from false beliefs in an interactive helping task. PloS one, 12(4), e0173793.
- [SPARK]Krupenye, C., & Call, J. (2019). Theory of mind in animals: Current and future directions. Wiley Interdisciplinary Reviews: Cognitive Science, 10(6), e1503. (25 pages)
Thursday, November 9, 2023: Prof
- Guest: Dr. Aida Nematzadeh
- [QALMRI] Nematzadeh, A., Burns, K., Grant, E., Gopnik, A., & Griffiths, T. L. (2018). Evaluating theory of mind in question answering. arXiv preprint arXiv:1808.09352.
Week 12: Consciousness and Sentience
Tuesday, November 14, 2023: Group
- [SPARK]Graziano, M. S., Guterstam, A., Bio, B. J., & Wilterson, A. I. (2020). Toward a standard model of consciousness: Reconciling the attention schema, global workspace, higher-order thought, and illusionist theories. Cognitive Neuropsychology, 37(3-4), 155-172.
- [SPARK] Lemoine, B. (2022). Is LaMDA Sentient? An Interview (21 pages)
Thursday, November 16, 2023
- Psychonomics Conference (No Class BUT assigned readings)
- [SPARK] Nagel, T. (1974). What is it like to be a bat?. The Philosophical Review, 83(4), 435-450.(17 pages)
- [SPARK] Tomasello, M. What is it like to be a chimpanzee?. Synthese 200, 102 (2022). https://doi.org/10.1007/s11229-022-03574-5
Week 13: Learning and Teaching
Tuesday, November 21, 2023: Solo
[QALMRI] Bridgers, S., Jara-Ettinger, J., & Gweon, H. (2020). Young children consider the expected utility of others’ learning to decide what to teach. Nature Human Behaviour, 4(2), 144-152.
[SPARK] Gweon, H., Fan, J., & Kim, B. (2023). Socially intelligent machines that learn from humans and help humans learn. Philosophical Transactions of the Royal Society A, 381(2251), 20220048.
Thursday, November 23, 2023
- Thanksgiving break! No class!
Week 14: Culture and Conventions
Tuesday, November 28, 2023: Solo
[QALMRI] Martin, D., Hutchison, J., Slessor, G., Urquhart, J., Cunningham, S. J., & Smith, K. (2014). The spontaneous formation of stereotypes via cumulative cultural evolution. Psychological Science, 25(9), 1777-1786.
[SPARK] Whiten, A., Biro, D., Bredeche, N., Garland, E. C., & Kirby, S. (2022). The emergence of collective knowledge and cumulative culture in animals, humans and machines. Philosophical Transactions of the Royal Society B, 377(1843), 20200306.
Thursday, November 30, 2023: Solo
[SPARK] Centola, D., & Baronchelli, A. (2015). The spontaneous emergence of conventions: An experimental study of cultural evolution. Proceedings of the National Academy of Sciences, 112(7), 1989-1994.
[SPARK]DeepMind Podcast: Better together(34 mins)
Sunday, December 3, 2023
- Project Milestone #5 (First Draft) due!
Week 15: Human Uniqueness
Tuesday, December 5, 2023: Solo
- [SPARK]Laland, K., & Seed, A. (2021). Understanding human cognitive uniqueness. Annual Review of Psychology, 72, 689-716.
Thursday, December 7, 2023: Prof
- It’s a wrap!
Sunday, December 17, 2023
- Project Milestone #6 (Final Project) due!
Grading
The grading scale for this class is as follows:
| Letter grade | Points |
|---|---|
| A | 95 - 100+ |
| A- | 90 - 94.99 |
| B+ | 87 - 89.99 |
| B | 83 - 86.99 |
| B- | 80 - 82.99 |
| C+ | 77 - 79.99 |
| C | 73 - 77.99 |
| C- | 70 - 72.99 |
| D | 60 - 69.99 |
| F | fewer than 60% |
Grades will be determined based on the following rubric, which is based on emphasizing our three learning goals (Evaluate, Synthesize, and Appreciate)
There are multiple ways for students to engage with class and course materials and achieve their desired grade. Students are encouraged to choose the assignments that work best for them. Course assessments that occur throughout the semester are designed to help students set and achieve their own goals for engaging in course content.
Points
| Component | Points | Learning goal |
|---|---|---|
| Weekly annotations | 10 | Evaluate, Synthesize |
| Weekly summaries | 20 | Evaluate, Synthesize |
| Class participation | 10 | Synthesize, Appreciate |
| Leading discussions | 20 | Evaluate, Synthesize, Appreciate |
| Final project | 40 | Evaluate, Synthesize |
| Extra credit | 5 | Appreciate |
| Total | 105 |
Weekly annotations (10 points)
For the research articles that you will read during the week, you are required to submit annotations and/or respond to your classmates’ annotations by 7 PM the day before class, using the Hypothes.is tool within Canvas. Annotations are visible to all classmates. One annotation is required per reading, but you are welcome to annotate more! Annotations should not exceed 50 words. The goal of these annotations is to stimulate the in-class discussions. Overall, these annotations contribute 10 points towards your final grade, but each annotation will be graded on a 1-point scale and then scaled to total up to 10 points at the end of the semester. The 1-point grading scale for each annotation is as follows:
| Descriptor | Points |
|---|---|
| Submitted a thoughtful annotation | 1 |
| Submitted a low-effort annotation | 0.5 |
| Did not submit an annotation | 0 |
Your annotations should reflect your engagement with the material and you are encouraged to ask thoughtful questions as you go. Annotations can be about any specific part of the reading/material, such as questions about the logic, clarity, technical soundness, as well as implications of the arguments, or even your reflections on any part of the reading. Treat these annotations as a first reaction to the content being discussed. Please remember to be thoughtful and respectful of your classmates’ ideas and opinions as you make and view annotations.
Note: You are not required to submit any annotations for the day you are scheduled to lead the discussion.
Weekly summaries (20 points)
The material we cover each class will either be an empirical article (that describes one or a series of experiments targeted towards one key question), a review paper (that consolidates many empirical articles), or a podcast (that discusses a range of articles and themes). Based on the material you select to reflect upon each week, you will be expected to produce ONE QALMRI or SPARK summary. The goal of this assignment is to allow you a chance to revisit the class discussion and respond to the material in a deeper manner.
Empirical article QALMRI: QALMRI is an acronym designed to help you understand the critical parts of an empirical research article. It stands for Question, Alternatives, Logic, Method, Results, and Inference. Please note that if an empirical paper has multiple experiments, you are required to submit a QALMRI that discusses the logic, methods, and results of each experiment in the paper in a comprehensive manner.
Review article/Podcast SPARK: SPARK is a tool designed to assist you in reading and reflecting on a review article or podcast. It stands for Subject, Perspectives, Analysis, Reflection, and Knowledge.
Please note that all assignments must be submitted before the due date each week (details on Canvas) to count towards the final grade - late submissions will NOT be accepted (unless you are using a flex day, see late work policy).
All QALMRI/SPARK summaries must be submitted via Canvas with clear details about which article/podcast is being summarized (the assigned materials list indicates whether an assigned material will require a QALMRI or SPARK). Overall, these summaries contribute 20 points towards your final grade, but each summary will be graded on a 5-point scale and then scaled to total up to 20 points at the end of the semester. The grading scale for each summary is as follows:
| Descriptor | Points |
|---|---|
| Outstanding, thoughtful assignment with no logical and/or writing flaws | 5 |
| Very good assignment with some minor flaws | 4 |
| Assignment demonstrates competency but some significant weaknesses | 3 |
| Assignment demonstrates competency but some major weaknesses | 2 |
| Does not meet expectations | 0-1 |
Class participation (10 points)
Students are encouraged to participate during class by responding to and reflecting on the course content, as well as engaging with other students via activities and group work. Your attendance will also count for some part of your class participation.
Overall, here is a breakdown of how class participation will be assessed:
| Component | Points |
|---|---|
| In-class participation and/or attending office hours | 2.5 |
| Providing feedback on class discussions | 5 |
| Attendance (attending 90% of classes) | 2.5 |
| 10 |
In-class participation will be assessed based on how engaged you are in or outside class - I will be looking for engagement via participating in in-class activities, asking questions, volunteering answers, etc. on an overall basis.
At the end of each class session where students are leading discussion, you will be asked to provide feedback for them via an anonymous survey. Filling out these surveys will count towards your class participation grade. Specifically, if you fill out 90% of these feedback surveys, you will earn 5 points. If you fill out 80% of these surveys, you will earn 4 points. If you fill out anything between 1-79% of these surveys, you will earn 3 points. If you fill out no surveys, you will earn 0 points.
Attendance will be taken for each class and you will get full credit if you attend at least 90% of the class sessions. Beyond that, you will be assigned partial credit based on the number of classes you miss, i.e., 0.5 point will be deducted for each 10% drop in attendance (e.g., if you attend 80% of the classes, you will earn 2 points out of 2.5, if you attend 70% of the classes, you will earn 1.5 points out of 2.5, etc.)
Leading discussions (20 points)
You will lead two discussions in this course: a solo discussion as well as one group discussion with one or two classmates. For all discussions, you are encouraged to get in touch with me a week BEFORE you are leading discussion to discuss your general plan for the discussion.
Please read these guidelines BEFORE our meeting so that you are best prepared with ideas and questions.
During class, you will be required to:
- Present a short (3-5 minute) summary of the assigned material, focusing on central themes, questions, and methods
- Synthesize your classmates annotations into 1-3 coherent themes and guide discussion on these themes during class by posing questions, moderating responses, and encouraging your classmates to think critically about the topic.
- Prepare an in-class activity for the group and encourage the class to reflect on the activity and how it connects to the assigned materials for this week. You can choose whether you want the class to engage in the activity before or after the discussion portion. You can brainstorm ideas for the class activity with me during our meeting.
- Summarize the in-class discussion.
You will be responsible for making sure the summaries, discussion, and in-class activities are all completed during class time. For joint discussions, you are welcome to assign roles (e.g., one person summarizes, other person moderates discussion, etc.) for different components, or plan and execute different components together as a team.
Below are some general resources for leading effective discussions:
- How to Lead a Class Discussion by Rachel Seidman
- Leading an Effective Discussion, Samuel Schaffer and Alison Green
- Active Learning Techniques, Duke University
Final Project (40 points)
You will also work on a final project for this class. You have three different options for your final project, these are briefly described below. More details about final projects are available at the links below and will also be discussed in class.
Project options
Minute Intelligence: For this project, you will create a 5-7 minute video on any aspect of intelligence that we did not cover but interests you. Your video should introduce the topic, examine its relevance to real life, and then describe the research that has been conducted on the topic so far in an engaging and educational manner. Details about different milestones for this project are available here.
Gamifying Intelligence: For this project, you will create a game that tests an aspect of intelligence we did not cover in class and submit a poster that summarizes your game’s motivations, methods, and results. The game can be single or multi-player, but you will need to specify (1) your target research question, (2) independent variable(s), (3) dependent variables, (4) expected patterns of behavior and how they correspond to the aspect of intelligence you are attempting to study, and (5) pilot/real results from participants who have played your game. The game should be playable in person (via index cards, etc.) or online (via a survey). Details about different milestones for this project are available here.
Intelligence Review:For this project, you will write a 10-page APA-style review paper on a specific aspect of intelligence that we have NOT covered in class. Your paper should introduce the topic, address the broad and specific questions on the topic, and then describe the research conducted on the topic through a coherent narrative. Details about different milestones for this project are available here.
Milestones
There will be several formative low-stakes milestones during the semester to ensure you are making steady progress towards the final project. Due dates for these milestones are available on Canvas. The breakdown of how the milestones contribute to your final project grade is below:
| Milestone | Points |
|---|---|
| Project selection | 2.5 |
| Selection of aspect of intelligence | 2.5 |
| QALMRI/SPARK for research articles | 10 |
| Project plan/outline | 5 |
| First draft | 2.5 |
| Final submission | 17.5 |
| Total | 40 |
Milestone 1: Project selection (2.5 points)
This assessment will happen relatively early in the semester to ensure that you are clear on the different demands of the project options. This assessment will be graded for thoughtful effort, i.e., I want to see that you have made an effort to select the option that best aligns with your goals for this class.
Milestone 2: Selection of aspect of intelligence (2.5 points)
This assessment will help you think about the particular instance of cognition that you might want to explore. Note that the aspect of intelligence you select will depend on the project you have selected, so this assessment may also involve describing some specifics of your project. This assessment will be graded for thoughtful effort, i.e., I want to see that you have made an effort to identify an instance of cognition that aligns well with the project you have selected.
Milestone 3: QALMRI for research articles (10 points)
This assessment will help you organize your literature review and structure your analysis and/or writing/designing. You will prepare a list of 1 review and 5 primary/empirical research articles relevant to your project and submit SPARK/QALMRI reports for each of the articles. This will help you understand the research articles in detail and enable you to ultimately connect ideas across readings.
Milestone 4: Project plan/outline (5 points)
This assessment is intended to help you organize your overall plan for the final project. The specifics of the plan/outline will vary based on your chosen project, but you will be required to submit a rough outline/plan. This assessment will be graded for thoughtful effort, i.e., I want to see that you are making steady progress on your project and are able to integrate the research articles you have read with key arguments/analyses.
Milestone 5: First draft (2.5 points)
This assessment is intended to provide you feedback on your nearly-final submission. The goal is to make sure you are on track to submitting a strong final project. This assessment will be graded for thoughtful effort, i.e., I want to see that you are making steady progress on your project.
Milestone 6: Final submission (17.5 points)
This final assessment will require you to submit your final project and all its components. The specifics of your submission will vary based on your chosen project, so please refer to the details of your project to make sure you submit all required materials.
Extra credit (5 points)
There will be some opportunities to earn extra credit during the semester. These opportunities are described below:
Complete class surveys (2 points) : There will be 4 surveys during the semester to gather your reflections and suggestions to improve the course. With the exception of the pre-class survey, all other surveys will be anonymous, and you will be able to earn 0.5 point for each survey you complete.
Win Discussion Dynamo (1 point): Each time you lead discussion in class, your peers will provide you feedback on the same. The two students who receive the highest overall discussion score during the semester for leading great discussions will earn 1 extra credit each.
Win Team Player (1 point) : For each class, your peers will also evaluate who stood out as a team player during class discussions and activities, by observing how you participate in groups and consider your peers’ perspectives. The student who receives the overall highest score at the end of the semester will earn 1 extra credit.
Win Memer of the Semester (1 point) : Each week, you will have the opportunity to submit a meme via Canvas, that reflects your experience with the course content of that week. Memes should be original, i.e., they should be course-specific and something you have created yourself and not simply found on the internet, although you are allowed to use common images/tropes from popular memes as a starting point. Memes also need to have a specific format, with the title of the learning module at the top of the meme (see Canvas). All memes will be gathered and sent to the class anonymously at the end of the semester for a survey, and the student(s) with the average highest score and the best scoring meme will both receive 1 additional point. Note: A student can only receive a maximum of 1 point through this mechanism, even if the same student has the highest average score in the context and the best scoring meme.
Course Policies
Academic honesty and plagiarism
We, as a class, will abide by the Bowdoin College Academic Honor Code. While you are encouraged to discuss ideas and thoughts with your classmates, plagiarism in any form will be subject to grade reductions and disciplinary action. Specifically, you are permitted to make use of online resources and/or search platforms. However, directly copying or adapting written material and/or your classmates’ answers or ideas will be considered plagiarism. This policy applies to both individual and group assignments.
Please refer to this page for a list of resources related to plagiarism and other academic integrity issues. Here is another helpful infographic about plagiarism that you are encouraged to go over.
Use of generative artificial intelligence tools
Acknowledgement: This policy about generative AI was generated using the Generative AI Syllabus Statement Tool provided by Seaver College
Generative artificial intelligence tools — software that creates new text, images, computer code, audio, video, and other content—have become widely available. Well-known examples include ChatGPT/Bard for text and DALL-E for images. This policy governs all such tools, including those released during our semester together. You may use generative AI tools for work in this course to help with idea generation, literature review, drafting, and other such academic work. If you do use generative AI tools on assignments in this class, you must properly document and credit the tools themselves. Cite the tool you used, following the pattern for computer software provided by the American Psychological Association (APA) guide. If you choose to use generative AI tools, please remember that they are typically trained on limited datasets that may be out of date. Additionally, generative AI datasets are trained on pre-existing material, including copyrighted material; therefore, relying on a generative AI tool may result in plagiarism or copyright violations. Finally, keep in mind that the goal of generative AI tools is to produce content that seems to have been produced by a human, not to produce accurate or reliable content; therefore, relying on a generative AI tool may result in your submission of inaccurate content. It is your responsibility as a scholar — NOT the tool’s — to assure the quality, integrity, and accuracy of work you submit in any college course. Although you have wide latitude to determine how you use generative AI tools in this course, you must be wary of unintentional plagiarism or fabrication of data. Please act with integrity, for the sake of both your personal character and your academic record.
Electronic devices
Most of our class time will be spent in active discussions and in-person/online activities. Therefore, while you are welcome to bring a Macbook/iPad to class please put away your device unless you are asked to refer to it by the discussion leader/moderator. Please make sure that your device is charged when you arrive to class. In order to minimize distractions, please close or exit out of all other programs except those needed during class, and put your Mac/iPad on “work” mode. All class time should be devoted to working on in-class activities and group projects.
Attendance: How many classes can you miss?
It not only benefits your learning, but benefits all of our learning to be present together in the same space. Class time is designed to take advantage of our presence together. To that end, your attendance will count towards your class participation.
Of course, emergencies (illness or family emergencies) can and do occur. Note: If you are sick, please stay home. However, I would greatly appreciate that you email me if you will be missing class. If you miss more than 2 classes and I haven’t heard from you, I will be in touch to check in on you. Hopefully you will have connections to other students in the class and can find out what you missed from a classmate. I will also try my best to upload slides and other course materials on the website and/or on Canvas.
Late Work Policy
Sometimes, life doesn’t go as planned and you have way too much going on to turn things in on time. That is OKAY! This course has the following policies for late work:
- Each student has 5 “flex” days that they can use at their discretion throughout the semester. You can use all 3 days at once for a single assignment and turn in one assignment 3 days late (with no questions asked), OR you can spread the love across different assignments.
- If you need to turn in work late and do not have any flex days left, I will consider extensions based on legitimate reasons, which ONLY include verified illnesses and/or family emergencies. In these cases, you are encouraged to reach out to me at least 24 hours in advance of the due date.
- Work that is handed in late beyond the flex days or without an approved extension will automatically be graded on 50% of the original points.
- Using ONE flex day means you get a 24-hour extension. Please note that this is a strict extension and any work that is handed in beyond 24 hours after a flex day was requested will either need to use an additional flex day or will be graded on 50% of the original points.
- To request a flex day, you can send me an email within the 24-hour extension window, or leave a comment on your submitted assignment on Canvas.
Inclusion
I will do my very best to ensure that students from all backgrounds and perspectives receive equitable access and opportunity in this course, that students’ learning needs be addressed both in and out of class, and that the diversity students bring to this class is viewed as a resource, strength, and benefit. I hope to employ materials and engage in activities and dialogue that are respectful of different aspects of your identity.
Religious Holidays
No student is required to take an examination or fulfill other scheduled course requirements on recognized religious holidays. Students are expected to declare their intention to observe these holidays at the beginning of the semester.
Accommodations
Students with documented Bowdoin-granted accommodations have a right to have these met. I encourage you to see me in the first 2 weeks of class to discuss how your accommodations may support your learning process in this course. I highly encourage all students to meet with me in the first few weeks of class to discuss your learning preferences, challenges you may face learning this semester, and how we can create an effective learning experience for you. If you are interested in learning more about accommodations please see Lesley Levy in the Office of Student Accessibility or visit Bowdoin’s website on accessibility-related policies and resources.
Counseling Resources
As a student, you may experience a range of issues that can cause barriers to learning, such as strained relationships, increased anxiety, alcohol/drug problems, feeling down, difficulty concentrating and/or lack of motivation. These mental health concerns or stressful events may lead to diminished academic performance or reduced ability to participate in daily activities. Bowdoin College is committed to advancing the mental health and well-being of its students. If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available. You can learn more about the broad range of confidential mental health services available on campus at this link. The Dean of Students Office is also a resource for students facing personal and academic challenges. I encourage you to reach out to the amazing people in the dean’s office for a meeting anytime.
Learning Resources
The Baldwin Center for Learning and Teaching offers peer-to-peer resources including mentors, Q-Tutors, and Writing Assistants. If you or your family are multilingual, you may also take advantage of Lisa Flanagan to work on writing and speaking assignments and projects. Tina Chong is available as an Academic Coach to work with you on goal setting, managing time, study habits and other strategies to support academic success. You are encouraged to make an appointment and learn more about how the Center can support your learning.
Other resources
If you are on a budget or would benefit from financial assistance of any kind at any point in the semester, I encourage you to contact your Dean and explore the Supplemental and Emergency Funding website. The Office of the Dean of Students has grant and loan funds available to remove financial barriers so that students can more fully access the Bowdoin experience or to assist students with unexpected financial needs.
Mandated Reporter
As a faculty member, I am considered a Responsible Employee, per the Student Sexual Misconduct and Gender Based Violence Policy. As a Responsible Employee I am required to report disclosures of sexual misconduct, dating violence, stalking, and/or sexual and gender-based harassment to Bowdoin’s Title IX Coordinator, Kate O’Grady. My reporting does NOT mean that any actions will be taken beyond Kate reaching out to you and trying to schedule a time to talk to see what assistance you might need to be successful as a student here at Bowdoin. For more information please check out Bowdoin’s Title IX page.