Tracking learning experiences with xAPI

Along with the digitalizing society, the education sector is undergoing changes. Especially in recent years, many educational institutions have - either on their initiative or out of necessity - adopted e-learning as an integral part of their learning process. This has been reflected in the development of learning environments from formal and static to more versatile and varied structures, where learners can develop their competencies flexibly regardless of time and location. The changes have provided opportunities to track and collect increasing amounts of learning-related data to understand learning and learners more comprehensively. This process however requires certain flexibility and interoperability between systems and applications, for diverse e-learning contents to be tracked, stored, and reported effectively. However, many of the current e-learning standards are relatively rigid and ineffective in providing capabilities for online/offline recording of learning experiences outside of LMS systems, as well as considering more versatile learning activities such as watching videos, playing mobile games, and informal learning tasks. The study discussed the capabilities of xAPI technology to encompass the development objectives and expectations for e-learning at the national level. The objective of the study was to clarify how the unique functionalities of xAPI can respond to the needs of the developing e-learning industry and what issues should be considered in the development of xAPI for it to become a nationally significant framework for tracking and monitoring learning events. Initially, a literature review was conducted, to search for information about e-learning, xAPI, and related key concepts in the research context. The features of xAPI were furthermore compared to other nationally significant e-learning standards and specifications to develop a comprehensive understanding of the research topic. On the basis of the literature review, a general understanding of the xAPI specification and its key features was created. These observations were compared to national expectations for the future of e-learning and analytics using empirics. Empirical data was collected through thematic interviews. The material was analyzed and combined with the results obtained from the literature. The empirical material was utilized to develop an understanding of the xAPI’s correspondence to the national e-learning expectations but also to test the suitability of xAPI for the digital service platform being developed in the target organization. The study discovered that xAPI is an e-learning-related technical programming specification that can enable different learning experiences and learning monitoring systems to communicate with each other effectively. Different learning activities such as watching a video, reading online material, or playing mobile games can be tracked and recorded with xAPI in a common database called LRS for further processing. xAPI provides communities and organizations an opportunity to analyze learning profoundly - not only based on scores and results - and therefore can deliver valuable information about the development of competencies to form a better overall picture of the entire learning experience. Compared to many other e-learning standards and specifications, xAPI provides a flexible and globally developing specification that has clear potential to evolve into a nationally significant e-learning standard and therefore provide the education sector with opportunities to better comprehend future learning needs.Digitalisoituvan yhteiskunnan myötä myös koulutussektori on jatkuvien muutosten alla. Erityisesti viime vuosien aikana valtava määrä oppilaitoksia on – joko omasta aloitteesta tai pakon edessä – adaptoinut e-oppimisen kiinteäksi osaksi opetusta, mikä on näkynyt oppimisympäristöjen kehityksenä muodollisista ja staattisista ympäristöistä monipuolisempiin ja vaihtelevimpiin rakenteisiin, joissa opiskelijoilla on mahdollisuus kehittää omaa tietotaitoaan ajasta ja paikasta joustavin menetelmin. Analytiikan näkökulmasta tämä on avannut mahdollisuuksia kerätä yhä enemmän oppimiseen ja opiskelijoihin liittyvää dataa ja sitä kautta ymmärtää oppimista syvällisemmin. Tämä vaatii kuitenkin tiettyä joustavuutta ja yhteentoimivuutta järjestelmien ja sovellusten välillä, jotta erilaisia e-oppimisen sisältöjä voidaan seurata, tallettaa ja raportoida tehokkaasti. Monet nykyisistä e-oppimisstandardeista ovat kuitenkin verrattain jäykkiä ja tehottomia tarjoamaan mahdollisuuksia oppimistapahtumien online/offline seurantaan ja tallentamiseen LMS järjestelmien ulkopuolella sekä huomioimaan verrattain yksinkertaisten asioiden kuten suoritusten ja tulosten seurannan ohella myös monipuolisemmat oppimistehtävät kuten videoiden katsomisen, mobiilipelien pelaamisen ja erilaiset epämuodolliset oppimistapahtumat. Tutkimuksessa selvitettiin, miten xAPI-teknologia kykenee vastaamaan e-oppimiseen kohdistuviin kehitystavoitteisiin ja odotuksiin kansallisella tasolla. Tutkimuksen tavoitteena oli selvittää kuinka xAPI:n ominaisuudet vastaavat digitalisaation myötä kehittyvän e-oppimisekosysteemin tarpeita ja mitä asioita on huomioitava xAPI:n kehityksessä, jotta siitä voisi muodostua kansallisesti merkittävä oppimistapahtumien seuranta- ja välitystyökalu. Tutkimuksen aluksi suoritettiin kirjallisuuskatsaus, jossa etsittiin tietoa e-oppimisesta, xAPI:sta ja näihin liittyvistä keskeisistä käsitteistä tutkimuskontekstissa. xAPI:n ominaisuuksia verrattiin myös muihin kansallisesti merkittäviin e-oppimisstandardeihin ja -spesifikaatioihin tutkimusaiheen kokonaisvaltaisen ymmärryksen kehittämiseksi. Kirjallisuuskatsauksen pohjalta luotiin yleiskäsitys xAPI spesifikaatiosta ja sen keskeisimmistä ominaisuuksista muihin kansallisesti merkittäviin e-oppimisen standardeihin peilaten. Näitä havaintoja verrattiin kansallisiin e-oppimisen ja analytiikkatiedon tulevaisuuden odotuksiin empirian avulla. Empiirinen aineisto kerättiin teemahaastatteluilla. Aineisto analysoitiin ja yhdistettiin kirjallisuuskatsauksen tuloksiin. Empiirisen aineiston avulla ymmärrystä sekä xAPI:n vastaavuudesta e-oppimisen odotuksiin, että sopivuudesta kohdeorganisaatiossa kehitettävän digitaalisen palvelualustan tarpeisiin kehitettiin lopulliseen muotoonsa. Tutkimuksessa saatiin selville, että xAPI on e-oppimiseen liittyvä ohjelmointirajapinta, jonka välityksellä erilaiset oppimiskokemukset ja oppimisenseurantajärjestelmät voivat keskustella keskenään tehokkaasti. Erilaiset oppimiskokemukset kuten videon katsominen, verkkomateriaalin lukeminen tai mobiilipelien pelaaminen voidaan kokonaisuudessaan jäljittää ja taltioida xAPI:n avulla jatkokäsittelyä varten erilliseen tietokantaan nimeltä LRS. xAPI antaa yhteisöille ja organisaatioille mahdollisuuden analysoida oppimista syvällisesti – ei vain suorituksiin ja tuloksiin pohjautuen – ja tarjoaa näin arvokasta tietoa muun muassa oppimisen kehittymisestä oppimistavoitteisiin nähden ja mahdollistaa siten entistä paremman kokonaiskuvan muodostamisen koko oppimiskokemuksesta. Moniin muihin e-oppimisen standardeihin ja spesifikaatioihin verrattuna xAPI tarjoaa joustavan ja kansainvälisesti kehittyvän spesifikaation, jolla on selkeät mahdollisuudet kehittyä kansallisesti merkittäväksi e-oppimisen standardiksi ja joka kykenee tarjoamaan koulutusalalle mahdollisuuksia vastata paremmin tulevaisuuden oppimistarpeisiin

Tracing the creation and evaluation of accessible Open Educational Resources through learning analytics

The adoption of Open Educational Resources (OER) has been continuously growing and with it the need to addressing the diversity of students’ learning needs. Because of that, OER should meet with characteristics such as the web accessibility and quality. Thus, teachers as the creators of OER need supporting tools and specialized competences. The main contribution of this thesis is a Learning Analytics Model to Trace the Creation and Evaluation of OER (LAMTCE) considering web accessibility and quality. LAMTCE also includes a user model of the teacher’s competences in the creation and evaluation of OER. Besides that, we developed ATCE, a learning analytics tool based on the LAMTCE model. Finally, it was carried out an evaluation conducted with teachers involving the use of the tool and we found that the tool really benefited teachers in the acquisition of their competences in creation and evaluation of accessible and quality OER.La adopción de Recursos Educativos Abiertos (REA) ha ido en aumento y con ello la necesidad de abordar la diversidad de necesidades de aprendizaje de los estudiantes. Por ello, los REA deben cumplir con características tales como la accesibilidad web y la calidad. Así, los profesores como los creadores de REA necesitan de herramientas de soporte y competencias especializadas. La principal contribución de la tesis es el modelo LAMTCE, un modelo de analíticas de aprendizaje para hacer seguimiento a la creación y evaluación de REA considerando la accesibilidad web y la calidad. LAMTCE también incluye un modelo de usuario de las competencias del profesor en creación y evaluación de REA. Además, se desarrolló ATCE, una herramienta de analíticas de aprendizaje que está basada en el modelo LAMTCE. Finalmente, se llevó a cabo un estudio con profesores involucrando el uso de la herramienta encontrando que ésta realmente benefició a los profesores en la adquisición de sus competencias en creación y evaluación de REA accesibles y de calidad

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

The impact of emotions on student participation in an assessed, online, collaborative activity

There is growing recognition of the importance of emotions in academic online learning contexts. However, there is still little known about the role of emotions in social and collaborative online learning settings, especially the relationship between emotions and student participation. To explore this relationship, this study used a prospective longitudinal research design to follow 46 distance learning students throughout a 3-week assessed, online, collaborative activity. This approach allowed the fluctuating and dynamic aspects of emotions to be explored as well as the relationship between emotions and student participation in the collaborative activity. Self-report data were gathered using a semistructured online diary at five time points throughout the task (once at the start of the collaborative activity, three times during the activity, and the final entry after the activity had finished). Findings revealed that learners generally perceived pleasant emotions (such as relief, satisfaction and enjoyment) to have positive impacts, or no impact, on participation, whereas unpleasant emotions (such as anxiety, frustration, and disappointment) were generally perceived to have negative impacts, or no impact, on participation. Interestingly, however, anxiety, and to a smaller extent frustration, were perceived by a number of students to have positive impacts during the activity. To conclude this paper, implications for educators are highlighted

The Big Five:Addressing Recurrent Multimodal Learning Data Challenges

The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback

Multimodal Challenge: Analytics Beyond User-computer Interaction Data

This contribution describes one the challenges explored in the Fourth LAK Hackathon. This challenge aims at shifting the focus from learning situations which can be easily traced through user-computer interactions data and concentrate more on user-world interactions events, typical of co-located and practice-based learning experiences. This mission, pursued by the multimodal learning analytics (MMLA) community, seeks to bridge the gap between digital and physical learning spaces. The “multimodal” approach consists in combining learners’ motoric actions with physiological responses and data about the learning contexts. These data can be collected through multiple wearable sensors and Internet of Things (IoT) devices. This Hackathon table will confront with three main challenges arising from the analysis and valorisation of multimodal datasets: 1) the data collection and storing, 2) the data annotation, 3) the data processing and exploitation. Some research questions which will be considered in this Hackathon challenge are the following: how to process the raw sensor data streams and extract relevant features? which data mining and machine learning techniques can be applied? how can we compare two action recordings? How to combine sensor data with Experience API (xAPI)? what are meaningful visualisations for these data

A COMPARISON BETWEEN MOTIVATIONS AND PERSONALITY TRAITS IN RELIGIOUS TOURISTS AND CRUISE SHIP TOURISTS

The purpose of this paper is to analyze the motivations and the personality traits that characterize tourists who choose religious travels versus cruises. Participating in the research were 683 Italian tourists (345 males and 338 females, age range 18–63 years); 483 who went to a pilgrimage travel and 200 who chose a cruise ship in the Mediterranean Sea. Both groups of tourists completed the Travel Motivation Scale and the Big Five Questionnaire. Results show that different motivations and personality traits characterize the different types of tourists and, further, that motivations for traveling are predicted by specific —some similar, other divergent— personality trait

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically