MD

Psyc305 Course Details and Overview

Psyc305 – The Developing Mind

Welcome to the Module

  • Instructor Information:

    • Dr Kirsty Dunn

    • Dr Jill Lany

    • Dr Katie Alcock

    • Module Coordinator: k.dunn@Lancaster.ac.uk

    • Office Location: C11

Course Structure

  • This course is divided into three main parts:

    • Kirsty: Prenatal and infant development

    • Jill: Cognitive and language development

    • Katie: Cross-cultural approaches to studying development

  • Format:

    • Lectures: Content delivery

    • Seminars: Skills for Critical Writing Assignment (CWA) and exam preparation

  • Key Issues in Developmental Psychology Discussed:

    • How can we explain development?

    • The inventiveness of methods for studying development

    • Exploring common themes surrounding what it means to be human

    • Engendering a sense of wonder about human development

Expectations

  • Engagement:

    • Emphasis on engaging, attending lectures and seminars punctually.

    • Encouragement for independent learning (127 hours suggested).

    • Fostering peer learning and friendships for enhanced course experience.

    • Utilizing discussion pages for better interaction and responses to queries.

    • Q and A sessions to promote understanding and clarity on topics.

Reminder about Communication

  • Communication Protocol:

    • Prompt replies to student queries via Moodle posts and emails.

    • Target response time: within 48 hours during weekdays (7 am to 7 pm).

    • Importance of subscribing to notifications on Moodle for updates.

    • Encouragement to ask questions in person or through Moodle discussion pages.

Key Changes in the Course

  • Based on student feedback:

    • Better linking of topics and digital engagement methods.

    • Building confidence with knowledge checks.

    • Incorporation of more summative assessment feedback.

    • Revision of Q and A session formats.

    • Utilization of videos as introductory tools before course onset.

Assessment Overview

  • Assignment Formats:

    • CWA: Requires analysis of one research paper and designing a follow-on study consolidating learned skills.

    • Exam: One-hour assessment requiring expansion on course learnings.

    • Marking Criteria to be available on Moodle (To Be Confirmed).

    • Feedback cover sheets will be provided for evaluation purposes.

AI RAG System at Lancaster University

  • Red Category: Prohibition of using Generative AI tools.

  • Amber Category: Permitted use of AI tools in an assistive capacity as authorized by the module tutor.

  • Green Category: AI tools integrated into assessments as required by the module tutor.

Concerns Regarding AI

  • Recent Industry Insights:

    • A survey indicated that nearly 48% of employers believe graduates misrepresent their abilities through AI usage in job applications.

    • Comment from Stephen Isherwood highlights the dissonance when new hires’ skills do not align with recruitment performance, leading to disrupted training and employment outcomes.

The Confidence-Competence Gap

  • The survey of 105 professionals showed:

    • 91% rated themselves as having above-average decision-making skills.

    • However, 45% acknowledged a lack of structured decision-making processes.

    • Emphasis on the need for expertise in decision-making, particularly in complex situations.

AI Doubles Down on Errors

  • Notable AI Impact and Culture:

    • The idiom "you can't lick a badger twice" signifies that one cannot deceive someone again after they have already been tricked.

    • The idiom "you can't catch a camel to London" represents tasks viewed as impossible or impractical.

Exam Preparation Notes

  • A reminder of the closed-book exam requirement.

  • Studies indicating detrimental effects of AI on skills development:

    • Fan et al., 2025; Farrokhynia et al., 2024; Gerlich, 2025; Kosmyna et al., 2025

    • Kosmyna et al. (2025) explores cognitive debt accumulation when using AI for academic tasks.

Building Skills while Using AI

  • Timing is critical in using AI for performance enhancement.

    • AI can improve task performance, but its use prior to one's contributions may reduce long-term motivation (Wu et al., 2025).

    • Generative AI can't create new content but relies on existing data.

    • Concerns regarding accuracy, potential bias, intellectual property, data privacy, and ethical use exist in AI applications. Creativity can only be enhanced by AI if the initial idea was human-generated (Lee and Chung, 2024).

    • AI use in clinical settings can bias physicians if the tools are employed before personal judgment (Wu et al., 2025).

Analogies in Life

  • Illustrations of Learning Progression:

    • Cars: Health and obesity analogy.

    • Vehicle Types: Automatic versus electric vehicles.

    • Mathematics: Counting before using calculators.

    • Pedestrian Safety: Safely using crosswalks.

    • Bicycles: Transitioning from traditional bikes to e-bikes.

    • Music Composition: Starting with ear-tuning before using autotuners.

    • Photography: Learning editing fundamentals before automated processes.

Future Proofing Your Career

  • Technology and Job Market Trends:

    • Concerns of over-dependence on technology in fields like lighting and theater, with older generations exploiting these issues.

    • AI’s potential replacement of roles such as paralegals affecting recruitment options.

    • Importance of adapting to ensure skills in guiding AI use rather than being driven by AI.

Reporting AI Use in Assignments

  • Requirements for reporting AI usage:

    • For Amber or Red modules, students must document:

    • AI tools utilized.

    • Specific implementation details.

    • Prompts used and outputs received.

    • Text influence on writing before and after AI intervention.

    • Potential academic reviews for unreported AI usage will occur; hence, transparency is essential.

Lecture 1: Prenatal and Infant Development

  • Instructor: Dr Kirsty Dunn

  • Focus on the research decisions in developmental psychology at Lancaster University.

Week 1 Learning Objectives

  • To understand research decision-making processes in developmental psychology.

  • To engage with current research questions addressed in laboratories.

  • To critically evaluate what various measures signify about development, using looking time as a key example.

  • The skills developed will directly support coursework assignments.

Looking Time Measurement

  • A common approach in developmental studies to assess violation of expectation (VoE).

    • Key Findings: Flush of Research:

    • Longer looking times indicate a violation of expectation, suggesting an understanding of physical principles.

    • Research references:

    • Number: Wynn (1992).

    • Object Permanence: Baillargeon (1987).

Alternative Explanations for Looking Time

  • Recognizing perceptual causes for prolonged looking (Haith, 1998; Hunter and Ames, 1988; Schoner & Thelan, 2006).

  • Exploring social looking as a metric for measuring expectations (Walden et al., 2007).

  • The need for distinguishing between perceptual responses and social interpretation of observed novelty.

  • Dunn et al. (2016) investigated the role of social looking in indexing novelty and VoE.

Procedure - Object Identity VoE

  • Investigated looking and social looking as indices of infant VoE.

  • Citation: Dunn, K. & Bremner, J. (2016) in the journal Developmental Science.

Results: Looking Time vs Social Looking

  • Conclusions drawn from studies emphasize:

    • Social looking specifically measures VoE, helping understand object stability.

    • Looking time could indicate both VoE and novelty simultaneously.

    • Future studies should differentiate looking due to novelty from looking driven by expectation violation.