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·    Methodically document each step of your data collection process, elucidating the rationale behind every decision.

·    Provide code snippets complemented by explanatory comments, ensuring that your data collection procedures are both transparent and reproducible.

Part I-B Data Exploration and Contextualisation (10 points)

·    Clean and tidy your data for the next steps. Please show your data wrangling process in detail.

·    Provide an exhaustive overview of the dataset you formed, encompassing characteristics such as dimensions, data types, and a comprehensive description of each variable.

·    Clarify the rationale behind your selection of the data  source, emphasising its potential significance in social sciences.

Assessment Part II

Part II-A Building an Interactive Dashboard with R Shiny (30 points)

·    Create an interactive dashboard using R Shiny that utilises the refined dataset. Embed your interactive dashboard in your Quarto document, thereby creating your HTML-based report with the  interactive  output. Please see an example (Quarto_with_Rshiny.qmd) in the submission area on Moodle.

·    Design and implement a minimum of three interactive visualisations within the R Shiny dashboard, derived from your dataset.

·    Offer clear and concise interpretations of each visualisation, elucidating any emerging trends, patterns, or noteworthy observations.

·    Elaborate on the specific visualisations chosen, justifying their selection, and elucidating their contributions to a deeper comprehension of the data source.

Part II-B Reproducibility (10 points)

·    Uphold the principles of reproducibility by sharing your replication materials in the compressed (zipped) folder, encompassing all pertinent code and a meticulously crafted README.md file. Prioritise the meticulous documentation of your codebase, rendering it accessible and comprehensible for potential replication.

Part II-C Critical Engagement with AI: ChatGPT (20 points)

You are expected to provide your reflections based on the points below in the report.

·    Embrace ChatGPT as a collaborative tool in your computational process, soliciting its code refinement.

·    Engage in a critical evaluation of ChatGPT's contributions to your project within a dedicated section of your report

·    Analyse the value-added by ChatGPT, highlighting instances where it offered insightful perspectives, refined code, or innovative problem-solving approaches.

·    Dilate upon any constraints or challenges that surfaced during interactions with ChatGPT, contributing to a well-rounded assessment.

·    Reflect upon how ChatGPT impacted your assessment's trajectory, shaping its outcome and affecting your overall learning experience.

AI-Usage Policy in This Assessment:

In this module/assignment, students are permitted to use only ChatGPT 3.5 for specific defined processes within the assessment.

This can be utilised to enhance and support the development of specific skills in specific ways, as specified by the module leader and required by the assessment. As per the requirements, for instance, students are asked to use ChatGPT for critically evaluating their code in automated data collection, data processing, and creating interactive dashboards in this assessment. In doing so, students are expected to highlight instances where ChatGPT offers insightful solutions, refined code, or worsens student’s solutions and code.

Except critical engagement with ChatGPT through code refinement, this module prohibits all other use of artificial intelligence (AI), including large language models, to author or co-author formative or summative work. This prohibition includes the following practices and any practices similar to them:

· Writing parts or all of an assessment;

· Generating outlines, structures and high-level arguments for essays;

· Rewriting or paraphrasing text from other sources for use in written work.

Language and writing review are not prohibited, defined as having a third-party or software check areas of academic writing such as structure, fluency, presentation, grammar, spelling, punctuation, and language translation. However, language review may be considered Academic Misconduct if substantive changes to content have been made by the reviewer or software or at their recommendation, which would suggest that the reviewer or software had either produced or determined the substantive content of the work.

Including content generated by AI tools will not be considered academic misconduct only if it is clearly signposted (by, for example, quotation marks) and attributed (by including a reference to the tool and date of use). However, similarly to quoting Wikipedia, quoting an AI system is unlikely to be a valuable addition to your work and unless clearly relevant to an argument may negatively impact the perceived quality of your work.

Suspected use of AI technologies other than specified one in the assessment may lead students to be subject to an Investigatory Viva.