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ARCH41310

Academic Year 2026/2027

Land / Landscape (ARCH41310)

Subject:
Archaeology
College:
Social Sciences & Law
School:
Archaeology
Level:
4 (Masters)
Credits:
10
Module Coordinator:
Dr Ryan Lash
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Landscape is a key concept in archaeology – and also among the most flexible.
In the most general sense, studies of landscape investigate human interactions with the natural and built elements of the lands we inhabit. Landscapes that exist today bear the traces of many millennia of human endeavours to sustain livelihoods and social formations. As such, landscapes provide essential resources for telling stories about our past.

This module will introduce students to fundamental methods and theories employed in landscape archaeology. Our focus will be on multi-disciplinary approaches that integrate scientific techniques, historical sources, and embodied experiences of landscapes. Through lectures, readings, activities, and field trips, students will learn to decipher archaeological landscapes and their power to engage the senses, evoke the past, and structure patterns of human action, affiliation, and imagination.

* Field trips for this module will include a day trip to Tara during week 1 and 2 field trips during week 8.

About this Module

Learning Outcomes:

1. Understand the range of methods and techniques used by archaeologists to study landscapes

2. Understand and apply theoretical frameworks used by archaeologists to analyse human engagements with landscapes

3. Develop first hand-experiences of Irish landscapes and employ publicly available resources and databases to decipher their stories

Indicative Module Content:

Methods of studying the landscape. Theoretical approaches to landscape. Interdisciplinary approaches. Field trips/discussions.

UNESCO highlights a set of key competencies that support individuals in their development and support society in achieving the UN Sustainable Development Goals (SDGs). UCD has adapted these competencies and is combining them with others to form a general framework of learning competencies. This module will help you develop the competencies below to the levels specified. 
Learning Competency Additional Information Level

Collaboration

 The ability to learn from others; to understand and respect the needs, perspectives and actions of others (empathy); to understand, relate to and be sensitive to others (empathic leadership); to deal with conflicts in a group; and to facilitate collaborative and participatory problem solving. Proficient

Critical Thinking

 The ability to question norms, practices and opinions; to reflect on one’s own values, perceptions and actions. Proficient

Systems Thinking

 The ability to recognize and understand relationships; to analyse complex systems; to think of how systems are embedded within different domains and different scales; and to deal with uncertainty. Proficient

Self-awareness

 The ability to reflect on one’s own role in the local community and (global) society; to continually evaluate and further motivate one’s actions; and to deal with one’s feelings and desires. Competent

Normative

 The ability to understand and reflect on the norms and values that underlie one’s actions; and to negotiate values, principles, goals, and targets, in a context of conflicts of interest and trade-offs, uncertain knowledge and contradictions. Competent

Digital Literacy and Judgement

 The ability to access, evaluate, create and communicate information in digital environments; to engage critically, ethically and responsibly with digital technologies and digital information; to understand their opportunities, limitations, risks and impact on individual’s digital identities; and to exercise informed judgement in digital participation and decision-making. Competent

AI Literacy & Agency

 The ability to understand, critically evaluate and responsibly engage with artificial intelligence; to recognise how AI systems are shaped by human values; to assess their ethical, social and environmental implications; and to exercise human judgement, agency and accountability in AI-related contexts. Novice

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


Goal Name Description Coverage

Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all 1

Achieve gender equality and empower all women and girls 1

Reduce inequality within and among countries 1

Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss 1
 

Student Effort Hours:
Student Effort Type Hours
Lectures

10
Small Group

8
Conversation Class

2
Field Trip/External Visits

30
Specified Learning Activities

75
Autonomous Student Learning

75
Total

200

Approaches to Teaching and Learning:
Lectures; In-class activities and discussions; Field Trips; Reflections on personal experiences of landscape

** Field Trips planned include a day trip to Tara during Week 1and two day trips during the week 8 study period. Details subject to change **

NOTE: Generative AI raises significant intellectual and ethical concerns, including its environmental impact, exploitation of workers in the Global South, and disregard for intellectual property. It also often fabricates non-existent citations, as well as content that is out-of-date or inaccurate. You may choose to use generative AI (Artificial Intelligence) to find, learn about and understand suitable resources (i.e. for background research), but remember that this can bring you down a confusing and incorrect path. You MUST AVOID the use of generative AI to compose or revise text. Any unattributed use of AI is forbidden and will put you in breach of UCD’s Student Plagiarism policies. Have confidence in your own reading, thoughts and voice.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): Decipher a Landscape (800 words)

Use historic maps, aerial imagery, folklore, and existing archaeological evidence to reconstruct the chronology of a landscape in one of four case-study options.		 Week 5 Graded No
30
 Yes
Assignment(Including Essay): Research Project (4,000 words)

Choose an archaeological monument and show how methods and theories of landscape could enhance understandings of human interactions and experiences in the past.		 Week 12 Graded No
70
 Yes

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.


Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Peer review activities
• Self-assessment activities

How will my Feedback be Delivered?

Written feedback within 4 weeks after submission deadline. Feedback contains feed-forward details, which will help you think about how you could improve your approach in future assignments. NOTE: Generative AI raises significant intellectual and ethical concerns, including its environmental impact, exploitation of workers in the Global South, and disregard for intellectual property. It also often fabricates non-existent citations, as well as content that is out-of-date or inaccurate. You may choose to use generative AI (Artificial Intelligence) to find, learn about and understand suitable resources (i.e. for background research). You MUST AVOID the use of generative AI to compose or revise text. Any unattributed use of AI is forbidden and will put you in breach of UCD’s Student Plagiarism policies.

Name Role
Dr Mark Haughton Lecturer / Co-Lecturer
Assoc Professor Helen Lewis Lecturer / Co-Lecturer
Assoc Professor Barry Molloy Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 6, 9, 10, 11, 12 Wed 14:00 - 15:50
Autumn Lecture Offering 1 Week(s) - 4, 5, 7 Wed 14:00 - 15:50
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