Handshake ecosystem for Educational Contents between Institutional Repository and OER based Repository

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Oppimisen tukeminen tieto- ja viestintätekniikan avulla II-asteella

Tutkimuksessa tarkastellaan tieto- ja viestintätekniikan tuomaa lisäarvoa kon-taktiopetukseen sekä Moodle verkko-oppimisalustan hyödyntämistapoja opet-tajan, oppijanja työelämäyhteistyön näkökulmista. Tutkimuksessa on kaksi päätavoitetta: selvittää yleiset verkko-opetusmallit ja verkko-opetusmalleja tukevat työkalut sekä selvittää Etelä-Kymenlaakson am-mattiopistossa käytössä olevan Moodle verkko-oppimisalustan nykyistä laaja-alaisempaan käyttöönottoon liittyvät haasteet ja kehitystarpeet. Kokemusten pohjalta jälkimmäisen tavoitteen suurimmaksi yksittäiseksi haasteeksi nousee verkko-opintojakson aloitus. Opettaja joutuu verkko-opintojakson käynnistämi-sen yhteydessä tekemään liikaa monimutkaisiamäärittelyjä. Kehitystarpeissa puolestaan haetaan ratkaisuja kysymykseen; mitenverkko-oppimisalusta mahdollistaa työelämäyhteyksien parantamisen ja miten se palvelee paremmin oppijoita verkko-opintojaksojen löytämisen suhteen. Tutkimuksen tuloksena rakentui uusi tapa verkko-opintojaksojen luomiseenja kategorisointiin. Kehitetyn toimintatavan ansiosta opettajan ei tarvitse enää luoda opintojaksoa verkko-oppimisalustaan, vaan niiden aihiot luodaan ohjel-mallisesti oppilashallintojärjestelmästä saatavista tiedoista muunnosohjelman välityksellä. Opettajan tehtäväksi jää vain materiaalin tuottaminen ja kyseisellä opintojaksolla tarvitsemiensa työkalujen alustaminen. Uudella kategorisointita-valla ja mielikuvitusrikkaammilla työtilojen hyödyntämistavoilla saavutetaan seuraavat edut: järjestelmä palvelee paremmin työelämäyhteistyötä, oppijoille selkeytyy oma opintokokonaisuus paremmin ja oppijoiden sekä opettajien on helpompi löytää verkko-oppimisalustassa olevat opintojaksot.

Interaktiivisen oppimisympäristön kehittäminen sähkötekniikan laboratoriotyöskentelyyn

Teklab is a manufacturer of electrical workstations. One major client group for the workstations is schools.Recently Teklab has started to concentrate on offering laboratory packages instead of single workstations. Laboratory packages include e.g. workstations, furniture, assembly and maintenance program. Teklab is looking for ideas to create more value for the laboratory package. One possibility is to design an educationalintroduction package to electric laboratories. In this thesis basic research isdone by studying the teaching methods in use today. Also modern education technology is presented. The thesis analyses different technologies for the laboratory introduction package. The technologies are analysed e.g. by applicability and feasibility. As a result of the work, the introduction has been done using an interactive presentation system. The presentation uses a software program and wireless student handsets designed by Dolphin Interactive. As a part of the work, also the recreation of the Teklab devices' instruction manuals has been started. For the future work, a digital learning object is under work, and a laboratory test is planned.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Emancipating and developing learning activity: Systemic intervention and re-instrumentation in higher education.

The central theme of this thesis is the emancipation and further development of learning activity in higher education in the context of the ongoing digital transformation of our societies. It was developed in response to the highly problematic mainstream approach to digital re-instrumentation of teaching and studying practises in contemporary higher education. The mainstream approach is largely based on centralisation, standardisation, commoditisation, and commercialisation, while re-producing the general patterns of control, responsibility, and dependence that are characteristic for activity systems of schooling. Whereas much of educational research and development focuses on the optimisation and fine-tuning of schooling, the overall inquiry that is underlying this thesis has been carried out from an explicitly critical position and within a framework of action science. It thus conceptualises learning activity in higher education not only as an object of inquiry but also as an object to engage with and to intervene into from a perspective of intentional change. The knowledge-constituting interest of this type of inquiry can be tentatively described as a combination of heuristic-instrumental (guidelines for contextualised action and intervention), practical-phronetic (deliberation of value-rational aspects of means and ends), and developmental-emancipatory (deliberation of issues of power, self-determination, and growth) aspects. Its goal is the production of orientation knowledge for educational practise. The thesis provides an analysis, argumentation, and normative claim on why the development of learning activity should be turned into an object of individual|collective inquiry and intentional change in higher education, and why the current state of affairs in higher education actually impedes such a development. It argues for a decisive shift of attention to the intentional emancipation and further development of learning activity as an important cultural instrument for human (self-)production within the digital transformation. The thesis also attempts an in-depth exploration of what type of methodological rationale can actually be applied to an object of inquiry (developing learning activity) that is at the same time conceptualised as an object of intentional change within the ongoing digital transformation. The result of this retrospective reflection is the formulation of “optimally incomplete” guidelines for educational R&D practise that shares the practicalphronetic (value related) and developmental-emancipatory (power related) orientations that had been driving the overall inquiry. In addition, the thesis formulates the instrumental-heuristic knowledge claim that the conceptual instruments that were adapted and validated in the context of a series of intervention studies provide means to effectively intervene into existing practise in higher education to support the necessary development of (increasingly emancipated) networked learning activity. It suggests that digital networked instruments (tools and services) generally should be considered and treated as transient elements within critical systemic intervention research in higher education. It further argues for the predominant use of loosely-coupled, digital networked instruments that allow for individual|collective ownership, control, (co-)production, and re-use in other contexts and for other purposes. Since the range of digital instrumentation options is continuously expanding and currently shows no signs of an imminent slow-down or consolidation, individual and collective exploration and experimentation of this realm needs to be systematically incorporated into higher education practise.

Learning Grasp Affordances from Vision

Monimutkaisissa ja muuttuvissa ympäristöissä työskentelevät robotit tarvitsevat kykyä manipuloida ja tarttua esineisiin. Tämä työ tutkii robottitarttumisen ja robottitartuntapis-teiden koneoppimisen aiempaa tutkimusta ja nykytilaa. Nykyaikaiset menetelmät käydään läpi, ja Le:n koneoppimiseen pohjautuva luokitin toteutetaan, koska se tarjoaa parhaan onnistumisprosentin tutkituista menetelmistä ja on muokattavissa sopivaksi käytettävissä olevalle robotille. Toteutettu menetelmä käyttää intensititeettikuvaan ja syvyyskuvaan po-hjautuvia ominaisuuksi luokitellakseen potentiaaliset tartuntapisteet. Tämän toteutuksen tulokset esitellään.

OpenAIRE compatibility for DSpace repositories

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Integrating Student Learning into the Repository Ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Building the ‘Digital’ Library: Routes to Managing our Institutional Digital Learning, Teaching and Research Assets Together

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Packaging Content for Aggregated and Federated Repositories through APTrust

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The ETH Zurich DOI Desk: DOIs as standard persistent identifier and best practice in Swiss Open Access repositories

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A museum object repository using LIDO schema

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Developing an introductory object-oriented programming course

The state of the object-oriented programming course in Lappeenranta University of Technology had reached the point, where it required changes to provide better learning opportunities and thus the learning outcomes. Based on the student feedback the course was partially dated and ineffective. The components of the course were analysed and the ineffective elements were removed and new methods were introduced to improve the course. The major changes included the change from traditional teaching methods to reverse classroom method and the use of Java as the programming language. The changes were measured by the student feedback, lecturer’s observations and comparison to previous years. The feedback suggested that the changes were successful; the course received higher overall grade than before.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.