Session chaired by Liam Doyle
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Adopting a Musical Intelligence and eLearning Approach to Improve the English Language Pronunciation of Chinese Students, by Luqi Wu (China) & Michael McMahon (Ireland).
Study was started because English language learning issues were found among students. There was invalid learning skills arising from the students learning the English language. Issues found included different accents among various lecturers.
The difference between English and Chinese languages include different tones and pitches. The e learning approach was used as an alternative approach using musical intelligence. Slide show includes objectives. Multiple intelligence include Interpersonal and Intrapersonal intelligences. Music and language include phenomes.
Elearning is a virtual learning environment which increases flexibility and saves time and costs. Saving up to 50% time and 80% costs of face to face learning.
Research Methods:
Both quantitative and qualitative data were used for collecting data. The case study used two groups both musical and traditional groups. The musical groups practiced with musical notes and native speaker pronunciation. The traditional groups only used native speaker translation.
Key Findings include:
1. All students achieve some degree of improvement
2. Musical intelligence students have greater improvement than non-musical intelligence in the same group
Limitations included:
- Researchers knowledge limitations
- No formal aptitude test for musical intelligence students.
- Case studies members’ regions limited
- The means of contacting Chinese English language teachers in China was limited
Future Research includes:
- Developing a structured online eLearning system for langugae is useful
- The application of social media to language learning
- The approach in relation to other language learning.
Conclusions:
Musical intelligence is a valid approach for Chinese students learning English and musical eLearning approach improves the pronunciation and accents of Chinese students.
Discussion:
The possible use of mobile phone apps for young children and other users
Each aspect can be further developed and it has tremendous potential
I-tunes company releases phrases etc with music. There are good options out there and it may be possible to continue this on further and is very helpful. Feedback system would be excellent.
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A Limited Engagement: A Case Study in Using Contextualised Online Learning Environments to Engage with Marginalised Communities, by Brian Caffrey & Peter Carew (Ireland).
To be added later – as Brian is our live blogger, this may be a little bit later than normal. It was however totally the best presentation in the entire seminar, possibly. Bias what now?
Amy is taking over so it may be less biased !
Rationale
Online learning environments can be a fundamental equaliser. For example, can overcome shyness issues. IIt can create an opportunity to fully actualise otherwise non-accessible learning opportunities.
SLD Population: They are increasingly stigmatized. Specific Learning Difficulty will be used for this study, for example, to ensure less stigmatizing and more empowering for students. SLD population are presented with socio- emotional barriers because of the ‘cognitive’ issues. The feeling of stigmatization does develop.
Registered students at third level educational institutes were selected as the cohort as there is easy access and also they are usually seen as ‘lost causes’ at this point in the education system.
The Online Support System, ‘Student Jam’ was gated and monitored to ensure data protection and for security precaution. This support system could be used in any manner they saw fit- socially or economically. The primary researcher monitored and facilitated the site, for example if bullying issues or if had a question regarding referencing etc. The tutor would answer any question except that involving the subject content exactly. Flat hierarchy devised to ensure that the tutor was on the same wavelength as them.
Intended goal was that participants became active stakeholders in their resource.
Initial findings:
- Very low participation levels- potential issues from this include: lack of cohort awareness, learned helplessness, passivity, technological issue- late reporting of this( when sorted out there was a 75% increase within 24 hours), the effect of re-activity, activation vs negative affecting
Changes then made to site based on feedback.
- Five themes emerged: Passivity, isolation, holism (integrate preexisting systems e.g. facebook)), potential( positively and negatively), stigma (data protection- particularly long term implications)
Passivity and Motivation Key explorations will include:
- The sense of mental difference: feel exclusion
- The nature and structure of the education system itself: lack of continuity in the learning
- the impact of hidden social geographies
- engaging with passivity: For example: needed to have a more active approach. E.G had to check the system three times a day at least.
Conclusion:
Future research must do much more to look at ways to address the population’s emotional concerns and well-being
A more longitudinal approach to research timeline would be recommended- three year minimum
Institutional support is necessary.
Discussion:
The task and involvement was not burdensome
The task could be improved by a person who has learning difficulties themselves.
Incentive questions: how one goes about this to a privilege to be involved.
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The Role of Causal Beliefs in Technology-Supported Policy Making, by Enrico Blanzieri (Italy).
Policy making. It is relevant for international stability, underlying European unification and it is gaining complexity in the European context.
Policy Making Process has several steps:
Agenda setting, policy formation*, decision making, implementation and evaluation.
*Focusing on policy formation.
Causal beliefs play an important role in policy making. The policy formed over false causal beliefs have the real possibility to fail. Causal beliefs have to be shared within the policy networks.
Models of public policy making processes do not involve specifically the role of supporting technology. There are three relevant aspects for policy making which were identified for technology:
- Evidence-based policy making. The policy maker should use evidence to form the policy. Technology plays a role to support the process with databases and resources collecting and organizing the evidence.
- Model-based policy making. There is usually a complex model which can be used that can be made available to policy makers. Van Delden et al (2011) have proposed a possible model. There needs to bridge the gap between science and policy. The model itself is not enough.
- Participatory policy making. This involves different actors. They do not usually share the goals or opinions of policy makers but the concerned with the forseen consequences of the policy. For example the role of technology could include social media.
Relevance of causal beliefs:
Causal beliefs can be true or false. On the other hand, those derived by hard data can be more reliable. The two ends of causal beliefs are: Causality and causality discovery. These are important topics in philosophy.
Belief literature is extremely wide with growing opinions of what beliefs are. E.G. between phsychology, philosophy, AI.
The main feature of beliefs is their subjectivity. You can believe something without knowing it.
From beliefs to causal beliefs: The characteristics are private or in other terms subjective. Causals beliefs are in principle falsifiable. Causal beliefs are very relevant in a lot of pshcological phenomenom.
The causal beliefs are important in two ways. They are relevant to policy making:
1. Affect both the policy makers and the population at large. Important to note this belief has a cultural nature.
2. A number of questions which require answers from social sciences. Software engineers have different questions.
Causal beliefs can represent AI, machine learning and statistical causal reference.
Support for the future. We think that causal beliefs are promising in the prospective of building technology aimed to support policy making.
Conclusions include:
Causal beliefs can play an important role in systems for supporting policy making.
It is a highly speculative claim but substantiated by literature.
Relevance of causal beliefs in relation to first paper on Sex trafficking and Supply Chain Systems.
Discussion:
Also include beliefs of other entities for example society.
Feedback, multiple connections and causal knowledge issues highlighted. As well as beliefs there is also knowledge. Response: Agree however, a lot of things we think are knowledge are actually beliefs. False beliefs also based on inaccurate data.
Wonderful presentation in the context of IFAC.
‘I believe that the sun is good for me, okay I will go out in the sun’ but will I follow that with the behavior? Or in relation to behavior. The link between intention and the actual behavior is important also. The group norm comes in and this leads to the intention, then do I follow the intention? The intention may never be followed up- gap there. Response: Causal beliefs don’t explain everything but they can be incorporated.
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If yould like to ask any questions, please feel free! Be sure to mention who you would like to direct them to.