Instructional goals
Grand Challenge 2 is the applied companion course to Methods of Social Research. It is designed to enable students to put into practice the main techniques introduced in the Methods of Social Research course through the development of a small-scale mixed-methods group research project on AI and academia.
The course aims to help students move from methodological knowledge to research implementation. In particular, students will formulate a feasible research question, translate it into a coherent research design, develop basic survey and interview instruments, collect empirical material responsibly, and present findings in a concise research dossier. The course also aims to strengthen collaborative research skills and to promote a responsible understanding of ethics in social research.
Participation in Methods of Social Research and Grand Challenge 2 during the same semester is an integral part of the course design.
Prerequisites
Participation in Methods of Social Research.
Intended learning outcomes
Knowledge and understanding
Students will acquire a practical understanding of how a social research project is designed and implemented in its initial stages. They will become familiar with the logic of mixed-methods research through the coordinated use of survey and interview techniques applied to a common topic.
Applying knowledge and understanding
Students will be able to formulate a focused research question, contribute to the design of a survey or interview-based component, participate in data collection, and integrate empirical evidence into a short research report.
Making judgements
Students will develop an awareness of the main methodological and ethical choices involved in basic social research, including question design, sampling feasibility, interviewing practice, anonymity, consent, and the responsible use of data.
Communication skills
Students will improve their ability to communicate research choices and findings in a clear and structured written form through the preparation of a group research dossier.
Learning skills
Students will strengthen their capacity to connect methodological concepts to real research practice, to work collaboratively in research teams, and to reflect critically on the opportunities and challenges posed by AI in academic life.
Course Contents
Grand Challenge 2 is an applied workshop linked to the Methods of Social Research course. Students work in groups on a small-scale mixed-methods research project focused on AI and academia, applying the methodological tools introduced in the parallel Methods of Social Research course.
The course begins by introducing the logic of mixed-methods research and the reasons for combining quantitative and qualitative techniques within a single project. It then presents AI and academia as a substantive research topic and introduces the ethical principles that govern social research involving human participants. The course combines common sessions for all students with method-specific labs for students assigned to either the quantitative or the qualitative component of the project. The quantitative component focuses on questionnaire design, sampling, and survey administration. The qualitative component focuses on interview design and interviewing practice.
Students work in groups of approximately ten members, normally divided into two coordinated sub-teams: one responsible for the survey component and one for the interview component. The course culminates in the submission of a group research dossier based on original empirical work on students’ uses, perceptions, and evaluations of artificial intelligence in university life.
Reference Books
Slides, readings, methodological guidelines, and other teaching materials distributed by the instructors during the course.
Teaching Methods
The course combines lectures, guided workshops, group-based research activities, and supervised project work. Some sessions are compulsory for all students, while the method-specific labs are compulsory only for students assigned to the relevant project component, although attendance remains open to all participants. The course is designed as an inquiry-based and practice-oriented learning experience closely integrated with the Methods of Social Research syllabus.
Assessment Method
Passing the course requires: regular attendance in all sessions marked as mandatory; attendance in the method-specific labs corresponding to the student’s assigned role in the group project; active contribution to the group research activities; and submission of the final group research dossier.
The final dossier must present the research question, research design, empirical tools used, main findings, ethical precautions adopted, and a short reflection on the strengths and limitations of the project. A pass will be awarded only to students who meet both the attendance requirements and the participation requirements connected to the group work.
Thesis assignment criteria
For theses in methods of social research, contact:
fvisconti@luiss.it or azinilli@luiss.it
Week 1
WEEK 1 >> Introduction to the course and to mixed-methods research. Presentation of the course structure, objectives, organization of group work, expected deliverables, and assessment criteria. Introduction to the logic of mixed-methods research and to the rationale for combining quantitative and qualitative techniques within a single project.
Week 2
WEEK 2 >> Artificial intelligence and academia as a research topic. Main debates, researchable dimensions, and possible empirical questions. This session is mandatory for all students.
Week 3
WEEK 3 >> Research ethics. Informed consent, anonymity, confidentiality, voluntary participation, and responsible data management. This session is mandatory for all students.
Week 4
WEEK 4 >> Qualitative component: what is a qualitative interview. Introduction to the logic of interviewing, the strengths of qualitative data, and the role of interviews in studying students’ experiences and evaluations of AI. This session is mandatory for all students.
Week 5
WEEK 5 >> Qualitative lab I: developing an interview guide. Practical workshop on identifying themes, writing open-ended questions, sequencing prompts, and ensuring comparability across interviews. Compulsory for students assigned to the interview component.
Week 6
WEEK 6 >> Qualitative lab II: conducting interviews. Practical training on interviewing techniques, interaction management, note-taking, recording procedures, and the responsible conduct of qualitative fieldwork.
Week 7
WEEK 7 >> Quantitative component: designing surveys on AI and academia. From a broad topic to a focused research question, variables, indicators, and questionnaire structure. This session is mandatory for all students.
Week 8
WEEK 8 >> Quantitative lab I: crafting effective questionnaire questions. Practical workshop on question wording, response options, clarity, ordering, and common sources of measurement error in survey research.
Week 9
WEEK 9 >> Quantitative lab II: sampling and survey administration. Introduction to basic sampling choices, target population definition, feasibility constraints, recruitment strategies, and the practical organization of survey fieldwork.
Week 10
WEEK 10 >> Self-managed time: fieldwork. Students work independently in groups to carry out data collection for the quantitative and qualitative components of the project.
Week 11
WEEK 11 >> Self-managed time: data analysis. Students organize, review, and interpret the material collected during fieldwork, preparing the basis for the integration of the two components of the project.
Week 12
WEEK 12 >> Lab III: integration of quantitative and qualitative results. Final workshop devoted to reflecting on how survey and interview findings can be combined within a single mixed-methods research design, and to preparing the final group research dossier.