Text (Instruction Step Text)
From The Embassy of Good Science
Describe the actions the user should take to experience the material (including preparation and follow up if any). Write in an active way.
- ⧼SA Foundation Data Type⧽: Text
2
The aim of training students in research ethics and integrity is to promote an understanding of ethical principles and practices in research. This includes exploring aspects of honesty, transparency, objectivity and accountability. Although at these levels, students are marginally involved in doing research, it is important to equip them with the knowledge and skills to conduct research responsibly, avoid misconduct such as plagiarism or falsification, comply with relevant regulations and guidelines, and uphold the integrity of the scientific community.
Resources for Bachelor and master students include (please see the last section of the BEYOND trainer guide for an overview of materials divided by topics and target groups):
*The [https://printeger.eu/upright/toc/obas-introduction/ introductory module][https://printeger.eu/upright/toc/ , and modules focusing specific RE and/or RI issues of the Upright training] developed by the [https://printeger.eu/ PRINTEGER] project
*The e-learning modules on [[Instruction:6ceba4e4-fb32-4953-9138-5436807fcde6|research integrity]], [[Instruction:86f47366-a189-4395-9301-36ddb6d1fc68|virtue ethics relevant for RI]], the series of introductory [[Instruction:17705907-d9b2-4f33-bc4f-088d84b4d971|videos]] and The [[Instruction:A0dd2e82-52e7-4030-a396-54525630e75c|Modified Rotterdam Dilemma Game]] developed by the [[Guide:Bbe860a3-56a9-45f7-b787-031689729e52|VIRT2UE]] project.
*The introductory videos and [https://www.path2integrity.eu/ri-materials information on the teaching methodology discussing research integrity and its significance], the series of learning cards ([https://www.path2integrity.eu/ri-materials Path2Integrity learning cards S]) focusing on bachelor students, alongside a dedicated handbook ([https://www.path2integrity.eu/ri-materials S-Series handbook]), and a series of learning cards ([https://www.path2integrity.eu/ri-materials Path2Integrity learning cards M]) focusing on bachelor students, alongside a dedicated handbook [https://www.path2integrity.eu/ri-materials (M-Series handbook]) developed byt the Path2Integrity project.
*The [https://en.researchethicscompass.net/ RID-SSISS training Foundation level] focuses on developing (but also helping learners to recall) central concepts of RE/RI
*The [https://www.academicintegrity.eu/wp/bridge/ BRIDGE project] [https://www.academicintegrity.eu/wp/bridge-modules-2/ training modules] and [https://www.academicintegrity.eu/wp/vignettes_interactive/ vignettes]
*The INTEGRITY project training tool for [https://h2020integrity.eu/toolkit/tools-undergraduate-students/integrity-games/ undergraduate].
*The [https://www.academicintegrity.eu/wp/bridge/ BRIDGE project] online games, board games, role-play games and scenarios game can be found [https://www.academicintegrity.eu/wp/bridge-games/ here].
*The [https://rosie-project.eu/ ROSiE] Training Materials for Responsible Open Science and the learning resources produced by the ROSIE project available on [https://rosie-project.eu/rosie-knowledge-hub/ ROSiE Knowledge Hub].
Trainers can select one or more of the following tools for evaluating training effectiveness for bachelor and master students.
{| class="wikitable"
|+Table 5: Tools for evaluating training effectiveness for bachelor and master students
!'''Tool for collecting learning outputs'''
!'''Details'''
!'''Analysis instrument **'''
|-
|'''ProLearning app'''
|''ProLearning'': https://www.epfl.ch/labs/chili/dualt/current-projects/realto/
<span lang="EN-GB"></span>
|learning analytics
|-
|'''Engagement app'''
|''ForgetNot'' (by EduLog): https://web.htk.tlu.ee/forgetnot
|learning analytics
|-
|'''Self-Reflection Form/Compass'''
|App under development, [https://docs.google.com/forms/d/1f4xNbQka73bfeDtwKCXTC5W5CoyhfVrtr4dwMXRNmWk/copy form] * (for copying and editing)
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Pre-post texts'''
|Collect a short text (e.g. a response to a case or short essay) before the training and after the training
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Learning diaries'''
|Ask learners keep a diary over a certain period, for each submission provide some guiding questions or topics
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Group reports'''
|Ask groups working together to provide a (short) group report (or provide a template with points to work on)
|SOLO taxonomy, content criteria
|-
|'''Group discussions'''
|Monitor the group discussions to evaluate the level of understanding and content discussed (scaffold as appropriate)
|SOLO taxonomy, content criteria
|-
|'''Group dynamics'''
|''CoTrack'' application: https://www.cotrack.website/en/
|learning analytics
|-
|'''Online learning platform'''
|Make use of accumulated authentic learning outputs in the learning platform
|statistics, SOLO taxonomy, reflection scale, content criteria
|-
|'''Domain-specific/ domain-transcending measure'''
|Use either of the two forms (WP4.2) measuring recognition and exemplifying of ethical issues
|statistics, SOLO taxonomy, content criteria
|-
|'''Retention check'''
|After a certain time (few weeks/months) ask learners to provide a short text (analysis of a case, short essay on an ethics topic/question). Compare the levels of understanding to another piece collected during or right after the training.[https://amsterdamumc-my.sharepoint.com/personal/g_inguaggiato_amsterdamumc_nl/Documents/!Oude%20N%20schijf/Documenten/Beyond/Training%20guide%20V7_GI.docx#_msocom_1 '"`UNIQ--nowiki-00000018-QINU`"'] [https://amsterdamumc-my.sharepoint.com/personal/g_inguaggiato_amsterdamumc_nl/Documents/!Oude%20N%20schijf/Documenten/Beyond/Training%20guide%20V7_GI.docx#_msocom_2 '"`UNIQ--nowiki-00000019-QINU`"']
|SOLO taxonomy, content criteria
|}
For instance, to measure participants’ reactions during or right after the training, ProLearning app or Self-Reflection Form can be used. In addition, if learners worked in groups so their group discussions can be monitored, and if they provided a group-report, the learning process can be evaluated based on the SOLO taxonomy to measure the levels of understanding. Moreover, if possible, a couple of months after the training an additional case study could be given to the same learners, and the content of their analysis could again be evaluated with the SOLO taxonomy. With this target group the domain-specific and domain-transcending measure could be implemented. This kind of effectiveness measure would give a possibility to triangulate the measurement in different time points.
An example for implementation can be found here: [https://helsinkifi.sharepoint.com/:p:/r/sites/BEYONDHelsinkiteam/Shared%20Documents/ENERI%20CR%20material%20example%20for%20ba_ma%20students.pptx?d=wdfb62d452de140f6a5a8df15611b48e2&csf=1&web=1&e=z2OYsx ENERI CR material example for ba_ma students.pptx]
'"`UNIQ--nowiki-0000001A-QINU`"' The Self-Reflection Form link enables the facilitator to make a copy of the form, which they can then edit and the data will accumulate on the facilitator’s cloud service (Google or Microsoft).
'"`UNIQ--nowiki-0000001B-QINU`"' Analysis instruments are described in WP4.2, later available at the Embassy’s website.
The BEYOND Trainer Guide introduces effectiveness measures to help trainers assess whether the training provided is impactful and beneficial. The versatile evaluation tools are designed to be applicable to various target groups and compatible with a variety of training activities and resources. Such evaluation measures are often absent in training resources, yet they provide trainers with a valuable mechanism to ensure how effectively training supports learning. Understanding how training facilitates learning and development is necessary in the process of fostering and strengthening integrity in the research community. Provision of training is a necessary component of the overall building of a culture of integrity. Yet training, the effects of which are not monitored, falls short of its potential to mirror the change it contributes to the research community. Therefore, in the orchard approach, learning and development provides important information about the readiness of the community to build a culture of integrity. Evaluating training effectiveness to ensure training programmes achieve their intended outcomes is crucial because it connects training investments to tangible results, ensuring that the effort put into developing and delivering training is worthwhile, and for pinpointing further development needs.
Effectiveness of research ethics and integrity (REI) training can be viewed through an established effectiveness framework, which identifies four outcome domains, namely:
1. reactions (participants’ self-assessment),
2. learning (knowledge, content),
3. behaviour (acting in the research community),
4. results (e.g. institutional outcomes).'"`UNIQ--ref-0000001C-QINU`"''"`UNIQ--ref-0000001D-QINU`"'
Evaluating development of ethical competencies should be determined through done as a system to get a more holistic picture. To do this, one can combine different forms of measurement, such as self-assessment and facilitator feedback as well as attitudes and behaviour treats (in tasks that display REI competencies in the research community, like research proposals, ethics sections of theses, articles, etc.). Furthermore, measurement could take place at different times to gain insight into the learning process, learning outcome, and long-term implications, namely:
• during the training (learning process),
• right after the training – students' and facilitator’s self-reports,
• later as part of another event or course where the display of REI competencies is expected (like RE section in theses and articles, research proposal, evaluation of RE situation in the department, etc.)
It is also important to consider what to do with the results, that is what kind of changes are necessary to improve teaching and/or the environment to build a culture of integrity.
Different tools can be used to collect various learning outputs and analysis instruments can be implemented to analyse the information that has been collected (Table 2). By analysis instruments we mean the taxonomies of learning and application of theoretical models, such as levels of reflection, ethical principles and so on (if data available are mainly in a qualitative format) or statistics and learning analytics (if the data are mainly in quantitative format).
{| class="wikitable"
|+Table 1: Tools and analytical instruments for collecting learning outputs in research ethics and integrity training
!Tool for collecting learning outputs
!Details
!Analysis instrument
|-
|'''''ProLearning'' app'''
|''ProLearning'': https://www.epfl.ch/labs/chili/dualt/current-projects/realto/
|learning analytics
|-
|'''Engagement app'''
|App under development, [https://forms.office.com/Pages/ShareFormPage.aspx?id=WXWumNwQiEKOLkWT5i_j7twYn7PlpvpDlgGDpz2LgIdUMk5XRTVYQTVKRFRDWDlHOUdGU1FHTUlFVi4u&sharetoken=03epmvYBRpmfXvpRg9os form] (for copying and editing)
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Self-Reflection Form/Compass'''
|App under development, [https://forms.office.com/Pages/ShareFormPage.aspx?id=WXWumNwQiEKOLkWT5i_j7twYn7PlpvpDlgGDpz2LgIdUMk5XRTVYQTVKRFRDWDlHOUdGU1FHTUlFVi4u&sharetoken=03epmvYBRpmfXvpRg9os form] (for copying and editing)
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Pre-post texts'''
|Collect a short text (e.g. a response to a case or short essay) before the training and after the training
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Learning diaries'''
|Ask learners keep a diary over a certain period, for each submission provide some guiding questions or topics
|SOLO taxonomy, reflection levels, content criteria
|-
|'''Group reports'''
|Ask groups working together to provide a (short) group report (or provide a template with points to work on)
|SOLO taxonomy, content criteria
|-
|'''Group discussions'''
|Monitor the group discussions to evaluate the level of understanding and content discussed (scaffold as appropriate)
|SOLO taxonomy, content criteria
|-
|'''Group dynamics'''
|''CoTrack'' application: https://www.cotrack.website/en/
|learning analytics
|-
|'''Online learning platform'''
|Make use of accumulated authentic learning outputs in the learning platform.
|statistics, SOLO taxonomy, reflection scale, content criteria
|-
|'''Domain-specific/ domain-transcending measure'''
|Use either of the two forms measuring recognition and exemplifying of ethical issues.
|statistics, SOLO taxonomy, content criteria
|-
|'''Retention check'''
|After a certain time (few weeks/months) ask learners to provide a short text (analysis of a case, short essay on an ethics topic/question). Compare the levels of understanding to another piece collected during or right after the training.
|SOLO taxonomy, content criteria
|-
|'''Vignettes'''
|This can be used for measuring ethical sensitivity in (non-)training context
|statistics, EASM (based on the SOLO taxonomy), content criteria
|-
|'''National surveys'''
|Can be used for analysing training-related content in reports and monitoring the display of REI leadership.
|statistics, REI leadership framework
|}
Evaluation tools can give further insight into the effectiveness of the training and materials proposed. This will help trainers to adjust training content and delivery methods to improve trainees’ learning experience and outcomes. We propose mixing various tools for collecting learning outputs and adjusting them to the intended target groups (throughout the training guide suggestions are provided on which tools would be most suitable for various target groups).
'"`UNIQ--references-0000001E-QINU`"'
Besides using Bloom’s Taxonomy to define learning objectives, the [https://www.johnbiggs.com.au/academic/solo-taxonomy/ SOLO Taxonomy] can be used .'"`UNIQ--ref-0000003E-QINU`"''"`UNIQ--ref-0000003F-QINU`"' The Structure of the Observed Learning Outcome, or SOLO, is a way to set the learning outcomes according to how complicated they are.'"`UNIQ--ref-00000040-QINU`"''"`UNIQ--ref-00000041-QINU`"' This allows us to evaluate students' work based on its quality following the idea of increasing understanding of complexities: Initially, we learn one or a few aspects of the task (unistructural), then multiple aspects that are unrelated to each other (multistructural), then we learn how to integrate them into a whole (relational), and lastly, we can generalise that whole to still-untaught applications (extended abstract). It evaluates the quality of students' work and understanding:
*<span lang="EN-GB">'''Pre-structural''': identify basic ethical concepts without fully understanding them.</span>
*<span lang="EN-GB">'''Unistructural''': recognize and label simple ethical procedures.</span>
*<span lang="EN-GB">'''Multistructural''': enumerate and describe ethical principles but struggle to connect them.</span>
*<span lang="EN-GB">'''Relational''': analyze and apply ethical concepts, understanding interrelations.</span>
*'''Extended abstract''': generalize and theorize ethical principles to solve novel dilemmas.
[[File:SOLOtaxonomy.png|alt=|center|frame|Fig 32. SOLO taxonomy (taken from Tammeleht & Löfström, 2023)]]
The SOLO taxonomy has been used to evaluate effectiveness of trainings as well as the development of ethical sensitivity and has been proven to be effective in the context of research ethics and integrity training.'"`UNIQ--ref-00000042-QINU`"''"`UNIQ--ref-00000043-QINU`"''"`UNIQ--ref-00000044-QINU`"''"`UNIQ--ref-00000045-QINU`"' The verbs emphasised in the descriptions below can be used as indicators of the appropriate levels in learning objectives.
''Pre-structural level (0)''
At the pre-structural level the learner fails to identify or approach topics in a meaningful way, but simply repeats the words in the question without understanding them.
''Unistructural level (1)''
At the unistructural level, the learner has sufficient knowledge to identify, recognise, count, find, label, match, name, and perform follow simple procedures. The learner identifies one relevant aspect displaying some familiarity with relevant concepts, but failing to outline multiple dimensions of it but failing to outline multiple dimensions of it. In the context of research ethics and integrity, this may mean identifying certain, perhaps common concepts, but having a limited view of them. For example, the learner may be able to identify some of the things that ought to be mentioned in an information letter to research participants but fails to understand all aspects of ensuring voluntary participation in research.
''Multi-structural level (2)''
At the multistructural level, the learner can enumerate, describe, illustrate, list, sequence, select, combine, and follow procedures, but struggles to make connections between concepts or draw conclusions based on interrelations. For example, the learner may understand that informed consent is necessary in research but fails to understand that this is so because of the need to respect people’s autonomy and right to make decisions that concern themselves.
''Relational level (3)''
At the relational level, the learner displays an ability to address the most relevant aspects of the concept and provide explanations pointing out interrelations and providing examples demonstrating their own reasoning. Corresponding action verbs include, analyse, apply, argue, compare, contrast, critique, explain causes, relate and justify. For example, the learner understands at least the main mechanisms and connections between FFP and the detrimental effects to science.
''Extended abstract level (4)''
At the extended abstract level, the coherent whole is generalised or re-conceptualised at a higher level of abstraction. The learner grasps a more abstract version of the concept, and recognises other domains to which the concept might be applied by displaying the ability to theorise, generate, generalise, hypothesise, create or reflect, formulate and reflect. For example, the learner is able to use knowledge about ethical analysis and ethical principles to solve a novel integrity-related dilemma, which the learner recognises is affecting a research group, but to which the learner has not been exposed before.
'"`UNIQ--references-00000046-QINU`"'
Besides using Bloom’s Taxonomy to define learning objectives, the [https://www.johnbiggs.com.au/academic/solo-taxonomy/ SOLO Taxonomy] can be used .'"`UNIQ--ref-00000061-QINU`"''"`UNIQ--ref-00000062-QINU`"' The Structure of the Observed Learning Outcome, or SOLO, is a way to set the learning outcomes according to how complicated they are.'"`UNIQ--ref-00000063-QINU`"''"`UNIQ--ref-00000064-QINU`"' In this way, the students' work can be assessed according to its quality and not according to how many parts they have understood correctly: initially, we learn one or a few aspects of the task (unistructural), then multiple aspects that are unrelated to each other (multistructural), then we learn how to integrate them into a whole (relational), and lastly, we can generalise that whole to still-untaught applications (extended abstract).
[[File:SOLOtaxonomy.png|alt=|center|frame|Fig 32. SOLO taxonomy (taken from Tammeleht & Löfström, 2023)]]
The SOLO taxonomy has been used to evaluate effectiveness of trainings as well as the development of ethical sensitivity and has been proven to be effective in the context of research ethics and integrity training.'"`UNIQ--ref-00000065-QINU`"''"`UNIQ--ref-00000066-QINU`"''"`UNIQ--ref-00000067-QINU`"''"`UNIQ--ref-00000068-QINU`"' The verbs emphasised in the descriptions below can be used as indicators of the appropriate levels in learning objectives.
''Pre-structural level (0)''
At the pre-structural level the learner fails to identify or approach topics in a meaningful way, but simply repeats the words in the question without understanding them.
''Unistructural level (1)''
At the unistructural level, the learner has sufficient knowledge to identify, recognise, count, find, label, match, name, and perform follow simple procedures. The learner identifies one relevant aspect displaying some familiarity with relevant concepts, but failing to outline multiple dimensions of it but failing to outline multiple dimensions of it. In the context of research ethics and integrity, this may mean identifying certain, perhaps common concepts, but having a limited view of them. For example, the learner may be able to identify some of the things that ought to be mentioned in an information letter to research participants but fails to understand all aspects of ensuring voluntary participation in research.
''Multi-structural level (2)''
At the multistructural level, the learner can enumerate, describe, illustrate, list, sequence, select, combine, and follow procedures, but struggles to make connections between concepts or draw conclusions based on interrelations. For example, the learner may understand that informed consent is necessary in research but fails to understand that this is so because of the need to respect people’s autonomy and right to make decisions that concern themselves.
''Relational level (3)''
At the relational level, the learner displays an ability to address the most relevant aspects of the concept and provide explanations pointing out interrelations and providing examples demonstrating their own reasoning. Corresponding action verbs include,analyse, apply, argue, compare, contrast, critique, explain causes, relate and justify. For example, the learner understands at least the main mechanisms and connections between FFP and the detrimental effects to science.
''Extended abstract level (4)''
At the extended abstract level, the coherent whole is generalised or re-conceptualised at a higher level of abstraction. The learner grasps a more abstract version of the concept, and recognises other domains to which the concept might be applied by displaying the ability to theorise, generate, generalise, hypothesise, create or reflect, formulate and reflect. For example, the learner is able to use knowledge about ethical analysis and ethical principles to solve a novel integrity-related dilemma, which the learner recognises is affecting a research group, but to which the learner has not been exposed before.
'"`UNIQ--references-00000069-QINU`"'
Examine the Rotterdam Dilemma Game cases and familiarize yourself with the classification criteria.'"`UNIQ--ref-00000002-QINU`"' Select the dilemmas you want to discuss. If using the Dilemma Game [https://www.eur.nl/en/about-eur/policy-and-regulations/integrity/research-integrity/dilemma-game app], start a new 'room' in group mode, creating a name for the room and specifying that it will be used for a 'lecture'. You will then be able to select the cases.
Please note that cases are grouped per topic. If the training is specifically aimed at reflecting on issues such as research processes, roles of different parties or publication ethics, the trainer might pick cases which correspond to those topics. Besides, while selecting the cases, take the attributes of the trainee group into account as well. For example, if you are going to play the game with a group of PhD students, then you should pick the cases suitable for them.
'"`UNIQ--references-00000003-QINU`"' +
Collaborative learning is a pedagogical approach that emphasises active participation, shared responsibility and mutual support among students. Collaborative learning is based on the idea that the production and internalisation of the knowledge is established by collaboration. Moreover, learning is usually best supported through social negotiation rarther than competition. Furthermore, team learning has been demonstrated to significantly enhance ethical practice. Research indicates that students primarily interpret their socialisation into academia and their field by the ethical standards and practices that they observe.'"`UNIQ--ref-0000005C-QINU`"''"`UNIQ--ref-0000005D-QINU`"''"`UNIQ--ref-0000005E-QINU`"'
When teaching research ethics and integrity, collaborative learning can be particularly effective as it can promote deeper understanding, critical thinking and ethical reasoning skills. In collaborative learning environments, students are actively engaged in the learning process rather than passively receiving information. They participate in discussions, debates and hands-on activities that require them to grapple with ethical dilemmas, analyse complex issues and apply ethical principles to real-world scenarios. This active engagement promotes deeper learning and retention of ethical concepts and principles. Collaborative learning encourages students to critically evaluate information, perspectives and arguments related to research ethics and integrity. Through discussions with peers, analysing case studies and reflecting on their own ethical beliefs and values, learners develop the ability to identify ethical issues, consider alternative viewpoints and make informed decisions.'"`UNIQ--ref-0000005F-QINU`"''"`UNIQ--ref-00000060-QINU`"''"`UNIQ--ref-00000061-QINU`"'
Collaborative learning environments provide opportunities for learners to challenge assumptions, explore ethical complexity and develop reasoned arguments based on evidence and ethical principles. Peer interaction is a central component of collaborative learning that allows learners to learn from each other's experiences, perspectives, and insights. By participating in discussions, debates, and collaborative projects with their peers, learners learn about various viewpoints, cultural perspectives, and disciplinary approaches to research ethics and integrity. Peer interaction also fosters collaboration, communication skills and teamwork, which are essential for addressing ethical challenges in research environments where collaboration and interdisciplinary cooperation are increasingly common.'"`UNIQ--ref-00000062-QINU`"''"`UNIQ--ref-00000063-QINU`"''"`UNIQ--ref-00000064-QINU`"'
During collaborating trainings, a variety of teaching methods can be used. Prior research has addressed collaborative learning with the use of case-based approaches, storytelling, flipped classroom, and role play and games (e.g., [https://www.erim.eur.nl/research-integrity/training-and-education/dilemma-game/ Rotterdam dilemma game]) .'"`UNIQ--ref-00000065-QINU`"''"`UNIQ--ref-00000066-QINU`"''"`UNIQ--ref-00000067-QINU`"''"`UNIQ--ref-00000068-QINU`"'
Collaborative approaches are utilised in [[Initiative:0582c7af-35eb-4def-b74e-c884f29965da|Path2Integrity]], [[Initiative:F9656f91-a514-44ff-9264-d6b3414fdddc|INTEGRITY]] and [[Initiative:8eed30fd-c2ed-44d1-9752-753092bd350e|VIRT2UE]].
'"`UNIQ--references-00000069-QINU`"'
Collaborative learning is a pedagogical approach that emphasises active participation, shared responsibility and mutual support among students. Collaborative learning is based on the idea that the production and internalisation of the knowledge is established by collaboration. Moreover, learning is usually best supported through social negotiation rarther than competition. Furthermore, team learning has been demonstrated to significantly enhance ethical practice. Research indicates that students primarily interpret their socialisation into academia and their field by the ethical standards and practices that they observe.'"`UNIQ--ref-0000008E-QINU`"''"`UNIQ--ref-0000008F-QINU`"''"`UNIQ--ref-00000090-QINU`"'
When teaching research ethics and integrity, collaborative learning can be particularly effective as it can promote deeper understanding, critical thinking and ethical reasoning skills. In collaborative learning environments, students are actively engaged in the learning process rather than passively receiving information. They participate in discussions, debates and hands-on activities that require them to grapple with ethical dilemmas, analyse complex issues and apply ethical principles to real-world scenarios. This active engagement promotes deeper learning and retention of ethical concepts and principles. Collaborative learning encourages students to critically evaluate information, perspectives and arguments related to research ethics and integrity. Through discussions with peers, analysing case studies and reflecting on their own ethical beliefs and values, learners develop the ability to identify ethical issues, consider alternative viewpoints and make informed decisions.'"`UNIQ--ref-00000091-QINU`"''"`UNIQ--ref-00000092-QINU`"''"`UNIQ--ref-00000093-QINU`"'
Collaborative learning environments provide opportunities for learners to challenge assumptions, explore ethical complexity and develop reasoned arguments based on evidence and ethical principles. Peer interaction is a central component of collaborative learning that allows learners to learn from each other's experiences, perspectives, and insights. By participating in discussions, debates, and collaborative projects with their peers, learners learn about various viewpoints, cultural perspectives, and disciplinary approaches to research ethics and integrity. Peer interaction also fosters collaboration, communication skills and teamwork, which are essential for addressing ethical challenges in research environments where collaboration and interdisciplinary cooperation are increasingly common.'"`UNIQ--ref-00000094-QINU`"''"`UNIQ--ref-00000095-QINU`"''"`UNIQ--ref-00000096-QINU`"'
During collaborating trainings, a variety of teaching methods can be used. Prior research has addressed collaborative learning with the use of case-based approaches, storytelling, flipped classroom, and role play and games (e.g., [https://www.erim.eur.nl/research-integrity/training-and-education/dilemma-game/ Rotterdam dilemma game]) .'"`UNIQ--ref-00000097-QINU`"''"`UNIQ--ref-00000098-QINU`"''"`UNIQ--ref-00000099-QINU`"''"`UNIQ--ref-0000009A-QINU`"'
Collaborative approaches are utilised in [[Initiative:0582c7af-35eb-4def-b74e-c884f29965da|Path2Integrity]], [[Initiative:F9656f91-a514-44ff-9264-d6b3414fdddc|INTEGRITY]] and [[Initiative:8eed30fd-c2ed-44d1-9752-753092bd350e|VIRT2UE]].
'"`UNIQ--references-0000009B-QINU`"'
Podcasting is not just about speaking. It is about how listeners process and follow information through sound.
Unlike written texts, listeners cannot go back to re-read a sentence, scan for key points or rely on visual structure. Because of this, podcasts require a different approach to communication.
When listening to a podcast, audiences process information in real time. They rely on structure and repetition to follow ideas, and interpret meaning through tone, emphasis, and pacing. If this structure is missing, it becomes easy to lose track of the message.
To support understanding, effective podcasts clearly introduce topics, guide listeners through ideas step by step, and repeat or summarise key points when needed. They also use small signals such as “so” or “what this means” to indicate transitions and help listeners stay oriented. +
Incorporating gender, health, and climate justice in your research: A reflexive question card exercise +
After the presentation, reflect on the following:
*Which of these four themes feels most relevant to your current research or study field?
*Can you identify a research decision (e.g., topic, method, interpretation) that might be shaped by your own position or assumptions?
* What is one insight or discomfort you experienced during the slides? +
Research shapes the world, not only through major discoveries, but also through the everyday choices we make, such as the questions we ask, the methods we use, and how we share our work. +
Research activities can take place in both wet and dry laboratories, each with distinct processes and environmental impacts.
Wet Laboratory (Wet Lab) Research Practice
A wet lab is a research environment where experiments are conducted using biological materials, chemicals, liquids, and specialized laboratory equipment. These activities often require substantial energy, generate plastic and chemical waste, and consume water and other resources.
Dry Laboratory (Dry Lab) Research Practice
A dry lab is a research environment where research is conducted through computational methods, including data analysis, modeling, simulations, and artificial intelligence. These activities rely on computers, data storage, and digital infrastructure rather than physical experiments.
While considerable attention has been given to reducing environmental impacts in wet laboratories, progress in digital or "dry lab" research has been slower. The growing use of data-intensive approaches in fields such as population health, personalized medicine, and artificial intelligence has increased the environmental footprint of digital research. Beyond the impacts associated with manufacturing computer hardware, digital technologies consume substantial amounts of energy through data centers, cloud storage, and high-performance computing.
Assessing these impacts is important not only for reducing greenhouse gas emissions but also because environmental sustainability considerations are increasingly being incorporated into research funding requirements, ethics frameworks, and research integrity guidelines. +
Doing research with communities affected by climate change: Climate-conscious methodologies matrix (for researchers and ethics reviewers) +
Please complete the multiple answers mini quiz +
<div><div>
<span lang="EN-GB">Develop clear and specific learning objectives for your session(s), aligned with the modules. '''Keep your specific context in mind in order to respond to the needs of the learners you wish to engage.'''</span>
</div><div>
'''<span lang="EN-GB">Expected learning outcomes are in line with the competence profile described in step 1 and may include:</span>'''
</div><div>
*'''<span lang="EN-US">Understand</span>''' <span lang="EN-US">the environmental, social, and ethical impact of research practices.</span>
</div><div>
*'''<span lang="EN-US">Recognize</span>''' <span lang="EN-US">the complexity and interconnected nature of sustainability challenges</span>
</div></div><div><div>
*'''<span lang="EN-US">Identify</span>''' <span lang="EN-US">opportunities to align research with societal and environmental priorities</span>
</div><div>
*'''<span lang="EN-US">Apply</span>''' <span lang="EN-US">practical strategies to make research more responsible and sustainable</span>
</div><div></div><div>
'''<span lang="EN-GB">Adapt your session to your audience.</span>''' <span lang="EN-GB">Not all materials are suitable for all learners.</span>
</div><div>
<span lang="EN-GB">Use the filtering functionality and consider the four stakeholder groups:</span>
</div><div>
*<span lang="EN-GB">Researchers</span>
</div><div>
*<span lang="EN-GB">Students</span>
</div><div>
*<span lang="EN-GB">Citizen scientists</span>
</div><div>
*<span lang="EN-GB">Ethics reviewers</span>
</div><div>
<span lang="EN-GB"> </span>
</div></div> +
Dialog Cards +
Dialog cards activity. +
[[File:Ext.Image20.png|center|frameless|600x600px]]
'''Ethics guidance and regulations'''
A not-for-profit organisation, The '''Metaverse Standards Forum''' brings together most of the industrial players involved in the metaverse, with the aim of creating the conditions for its worldwide interoperability:https://metaverse-standards.org/
'''AI Act: the EU AI Act of April 2021''' included in its annex the following statement:
Annex III, article 1: “Biometric identification and categorization of natural persons: (a) AI systems intended to be used for the ‘real-time’ and ‘post’ remote biometric identification of natural persons;” This statement applies in part to XR, to the collection of biometric data during the user's real-time 3D experience. The January 2024 version of the same AI Act further emphasises risks related to biometric categorisation and emotion recognition, and is also relevant for XR. https://artificialintelligenceact.eu/
'''Council of the European Union,''' Proposal for a Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts, paragraph 16, 2022: “AI systems deploy subliminal components such as audio, image, video stimuli that persons cannot perceive as those stimuli are beyond human perception or other subliminal techniques that subvert or impair person’s autonomy, decision-making or free choices in ways that people are not consciously aware of, or even if aware not able to control or resist, for example in cases of machine-brain interfaces or virtual reality.”
Basdevant, A, François, C, Ronfard, R. (2022) Mission exploratoire sur les métavers. Rapport interministériel. France. Available at:
[https://www.economie.gouv.fr/files/files/2022/Rapport-interministeriel-metavers.pdf https://www.economie.gouv.fr/files/files/2022/Rapport-interministeriel-] [https://www.economie.gouv.fr/files/files/2022/Rapport-interministeriel-metavers.pdf metavers.pdf]
IEEE SA - The IEEE Global Initiative on Ethics of Extended Reality: https://standards.ieee.org/industry-connections/ethics-extended-reality/
INRIA’s Website: https://www.inria.fr/en/how-does-virtual-reality-works
Techethos website (page on Digital XR): https://www.techethos.eu/digital-extended-reality/
The Open AR Cloud Code of Conduct: https://www.openarcloud.org/documents/code-of-conduct
XR Safety Initiative (XRSI) ethical guidelines for developers, users, and organizations: https://xrsi.org/xrsi-code-of-conduct
Zhu, L (2022) The Metaverse: Concepts and Issues for Congress. Congressional Research Service. Available at: https://sgp.fas.org/crs/misc/R47224.pdf.
'''Videos'''
Kent Bye’s XR Ethics Manifesto: https://www.youtube.com/watch?v=CXgY3YXxqJ8
Masterclass on XR in the classroom (Central Queensland University, Australia): [https://www.studyaustralia.gov.au/english/masterclasses/extended-reality-xr-in-the-classroom https://www.studyaustralia.gov.au/english/masterclasses/extended-] [https://www.studyaustralia.gov.au/english/masterclasses/extended-reality-xr-in-the-classroom reality-xr-in-the-classroom]
'''Bibliography'''
Adomaitis, L., Grinbaum, A., Lenzi, D. (2022) Identification and Specification of Potential Ethical Issues and Impacts and Analysis of Ethical Issues. https://doi.org/10.5281/zenodo.7619852.
Aucouturier E, Grinbaum A (2023) Recommendations to address ethical challenges from research in new technologies. CEA - Commissariat à l’énergie atomique et aux énergies alternatives. Available at: https://cea.hal.science/cea-04293426
Behr, K. M., Nosper, A., Klimmt, C., & Hartmann, T. (2005). Some practical considerations of ethical issues in VR research. Presence, 14(6), 668-676.
Fox, D., & Thornton, I. G. (2022). White Paper-The IEEE Global Initiative on Ethics of Extended Reality (XR) Report--Extended Reality (XR) Ethics and Diversity, Inclusion, and Accessibility. The IEEE Global Initiative on Ethics of Extended Reality (XR) Report--Extended Reality (XR) Ethics and Diversity, Inclusion, and Accessibility, 1-25.
Grinbaum, A., & Adomaitis, L. (2022). Moral equivalence in the metaverse. NanoEthics, 16(3), 257-270.
Kröger, J. L., Lutz, O. H. M., & Müller, F. (2020). What does your gaze reveal about you? On the privacy implications of eye tracking. In IFIP International Summer School on Privacy and Identity Management (pp. 226-241). Springer, Cham.
In the context of uncertainty, researchers should review their study protocols regularly to ensure that new findings are taken into account as they emerge +
In this lecture, Olivier Le Gall examines open peer review, highlighting both its benefits and potential risks. The presentation starts by elucidating the rationale behind open peer review, and proceeds to discuss its benefits as well as the associated risks of opening it.
'''Watch the lecture and then answer the questions.'''
'''Further reading:'''
The Embassy of Good Science: “[[Theme:Ecc7ac02-6e53-4634-b053-91045c50390c|Open peer review - transparent way of gatekeeping science]]”
Schmidt, B., Ross-Hellauer, T., Edig, X. van, & Moylan, E. C. (2018). Ten considerations for open peer review (7:969). F1000Research. https://doi.org/10.12688/f1000research.15334.1
Ross-Hellauer, T., & Horbach, S. P. J. M. (2024). Additional experiments required: A scoping review of recent evidence on key aspects of Open Peer Review. Research Evaluation, 33, rvae004. https://doi.org/10.1093/reseval/rvae004
Henriquez, T. (2023). Open peer review, pros and cons from the perspective of an early career researcher. mBio, 14(5), e01948-23. https://doi.org/10.1128/mbio.01948-23 +
During pandemics, researchers may experience a heightened risk of hostility and related safety and security concerns. Research ethics committees should check that risk management plans are in place +
In this lecture, Elina Koivisto addresses the topics of open access, open access publishing, and predatory practices. The first segment of the lecture provides a definition of open access, showcases various types of open access, and elucidates their distinctions. The subsequent segment explores the advantages of open access as well as some negative consequences associated with publishing in general and open access publishing specifically. The concluding segment is dedicated to predatory practices;it defines these practices and offers guidance on how to avoid them.
'''Watch the lecture and then answer the questions.'''
'''Further reading:'''
The Embassy of Good Science: “[[Theme:49d71148-0df2-4a78-93d4-c802b48bbdb7|Predatory publishing]]”
Beall, J. (2015). Criteria for determining predatory open access publishers. https://beallslist.net/wp-content/uploads/2019/12/criteria-2015.pdf
COPE Council (2019). COPE Discussion Document: Predatory Publishing. https://doi.org/10.24318/cope.2019.3.6 +
