Virtuaalimaailmoja valtaamassa : verkko-opetusinnovaation leviäminen koulun maantieteeseen vuosituhannen vaihteessa

Tutkimus käsittelee verkko-opetusinnovaation leviämistä perusasteen ja lukion maantieteeseen vuosina 1998–2004. Työssä sovellettiin opetusinnovaation leviämismallia ja innovaatioiden diffuusioteoriaa. Aineisto hankittiin seitsemänä vuotena kyselylomakkeilla maantieteen verkko-opetuksen edelläkävijäopettajilta, jotka palauttivat 326 lomaketta. Tutkimuksen pääongelmat olivat 1) Millaisia edellytyksiä edelläkävijäopettajilla on käyttää verkko-opetusta koulun maantieteessä? 2) Mitä sovelluksia ja millä tavoin edelläkävijäopettajat käyttävät maantieteen verkko-opetuksessa? 3) Millaisia käyttökokemuksia edelläkävijäopettajat ovat saaneet maantieteen verkko-opetuksesta? Tutkimuksessa havaittiin, että tietokoneiden riittämätön määrä ja puuttuminen aineluokasta vaikeuttivat maantieteen verkko-opetusta. Työssä kehitettiin opettajien digitaalisten mediataitojen kuutiomalli, johon kuuluvat tekniset taidot, informaation prosessointitaidot ja viestintätaidot. Opettajissa erotettiin kolme verkko-opetuksen käyttäjätyyppiä: informaatiohakuiset kevytkäyttäjät, viestintähakuiset peruskäyttäjät ja yhteistyöhakuiset tehokäyttäjät. Verkko-opetukseen liittyi intensiivisiä myönteisiä ja kielteisiä kokemuksia. Se toi iloa ja motivaatiota opiskeluun. Sitä pidettiin rikastuttavana lisänä, joka haluttiin integroida opetukseen hallitusti. Edelläkävijäopettajat ottivat käyttöön tietoverkoissa olevaa informaatiota ja sovelsivat työvälineohjelmia. He pääsivät alkuun todellisuutta jäljittelevien virtuaalimaailmojen: satelliittikuvien toistaman maapallon, digitaalikarttojen ja simulaatioiden käytössä. Opettajat kokeilivat verkon sosiaalisia tiloja reaaliaikaisen viestinnän, keskusteluryhmien ja ryhmätyöohjelmien avulla. Mielikuvitukseen perustuvat virtuaalimaailmat jäivät vähälle sillä opettajat eivät juuri pelanneet viihdepelejä. He omaksuivat virtuaalimaailmoista satunnaisia palasia käytettävissä olevan laite- ja ohjelmavarustuksen mukaan. Virtuaalimaailmojen valtaus eteni tutkimuksen aikana digitaalisen informaation hyödyntämisestä viestintäsovelluksiin ja aloittelevaan yhteistyöhön. Näin opettajat laajensivat virtuaalireviiriään tietoverkkojen dynaamisiksi toimijoiksi ja pääsivät uusin keinoin tyydyttämään ihmisen universaalia tarvetta yhteyteen muiden kanssa. Samalla opettajat valtautuivat informaation kuluttajista sen tuottajiksi, objekteista subjekteiksi. Verkko-opetus avaa koulun maantieteelle huomattavia mahdollisuuksia. Mobiililaitteiden avulla informaatiota voidaan kerätä ja tallentaa maasto-olosuhteissa, ohjelmilla sitä voidaan muuntaa muodosta toiseen. Internetin autenttiset ja ajantasaiset materiaalit tuovat opiskeluun konkretiaa ja kiinnostavuutta, mallit, simulaatiot ja paikkatieto havainnollistavat ilmiöitä. Viestintä- ja yhteistyövälineet sekä sosiaaliset informaatiotilat vahvistavat yhteistyötä. Avainsanat: verkko-opetus, internet, virtuaalimaailmat, maantiede, innovaatiot

Visual Impairment in Finnish Children : Prevalence, causes and morbidity of full-term and preterm children with visual impairment born from 1972 through 1989

The prevalence and the causes of childhood visual impairment in Finland during the 1970s and the 1980s were investigated, with special attention to risk factors and further prevention of visual impairment in children. The primary data on children with visual impairment were obtained from the Finnish Register of Visual Impairment, one of the patient registers kept up by the National Research and Development Centre for Welfare and Health (Stakes). The data were supplemented from other registers in Stakes and from patient records of the children in Finnish central hospitals. Visual impairment had been registered in 556 children from a population of 1,138,326 children between ages 0-17, born from 1972 through 1989. The age-specific prevalence of registered visual impairment was 49/100,000 in total. Of them, 23/100,000 were blind children and 11/100,000 were children born prematurely. Boys were impaired more often and more severely than girls. Congenital malformations (52%), systemic diseases (48%), and multiple impairments (50%) were common. The main ophthalmic groups of visual impairment were retinal diseases (35%), ocular malformations (29%), and neuro-ophthalmological disorders (29%). Optic nerve atrophy was the most common diagnosis of visual impairment (22%), followed by congenital cataract (11%), retinopathy of prematurity (10%), and cerebral visual impairment (8%). Genetic factors (42%) were the most common etiologies of visual impairment, followed by prenatal (30%) and perinatal (21%) factors. The highest rates of blindness were seen in cerebral visual impairment (83%) and retinopathy of prematurity (82%). Retinopathy of prematurity had developed in the children born at a gestational age of 32 weeks or earlier. Significant risks for visual impairment were found in the association with preterm births, prenatal infections, birth asphyxia, neonatal respiratory difficulties, mechanical ventilation lasting over two weeks, and hyperbilirubinemia. A rise in blind and multi-impaired children was seen during the study period, associating with increases in the survival of preterm infants with extremely low birth weight. The incidence of visual impairment in children born prematurely was seven times higher than in children born at full term. A reliable profile of childhood visual impairment was obtained. The importance of highly qualified antenatal, neonatal, and ophthalmological care was clearly proved. The risks associated with pre- and perinatal disorders during pregnancy must be emphasized, e.g. the risks associated with maternal infections and the use of tobacco, alcohol, and drugs during pregnancy. Obvious needs for gene therapies and other new treatments for hereditary diseases were also proved.

Psykoterapian vaikutusten arvioiminen : Keskustelunanalyttinen tutkimus arviointihaastattelun käytänteistä

In the field of psychiatry semi-structured interview is one of the central tools in assessing the psychiatric state of a patient. In semi-structured interview the interviewer participates in the interaction both by the prepared interview questions and by his or her own, unstructured turns. It has been stated that in the context of psychiatric assessment interviewers' unstructured turns help to get focused information but simultaneously may weaken the reliability of the data. This study examines the practices by which semi-structured psychiatric interviews are conducted. The method for the study is conversation analysis, which is both a theory of interaction and a methodology for its empirical, detailed analysis. Using data from 80 video-recorded psychiatric interviews with 16 patients and five interviewers it describes in detail both the structured and unstructured interviewing practices. In the analysis also psychotherapeutic concepts are used to describe phenomena that are characteristic for therapeutic discourse. The data was received from the Helsinki Psychotherapy Study (HPS). HPS is a randomized clinical trial comparing the effectiveness of four forms of psychotherapy in the treatment of depressive and anxiety disorders. A total of 326 patients were randomly assigned to one of three treatment groups: solution-focused therapy, short-term psychodynamic psychotherapy, and long-term psychodynamic psychotherapy. The patients assigned to the long-term psychodynamic psychotherapy group and 41 patients self-selected for psychoanalysis were included in a quasi-experimental design. The primary outcome measures were depressive and anxiety symptoms, while secondary measures included work ability, need for treatment, personality functions, social functioning, and life style. Cost-effectiveness was determined. The data were collected from interviews, questionnaires, psychological tests, and public health registers. The follow-up interviews were conducted five times during a 5-year follow-up. The study shows that interviewers pose elaborated questions that are formulated in a friendly and sensitive way and that make relevant patients' long and story-like responses. When receiving patients' answers interviewers use a wide variety of different interviewing practices by which they direct patients' talk or offer an understanding of the meaning of patients' response. The results of the study are two-fold. Firstly, the study shows that understanding the meaning of mental experiences requires interaction between interviewer and patient. It is stated that therefore semi-structured interview is both relevant and necessary method for collecting data in psychotherapy outcome study. Secondly, the study suggests that conversation analysis, enriched with psychotherapeutic concepts, offers methodological possibilities for psychotherapy process research, especially for process-outcome paradigm.

Methods in general model localization

The aim of this study was to evaluate and test methods which could improve local estimates of a general model fitted to a large area. In the first three studies, the intention was to divide the study area into sub-areas that were as homogeneous as possible according to the residuals of the general model, and in the fourth study, the localization was based on the local neighbourhood. According to spatial autocorrelation (SA), points closer together in space are more likely to be similar than those that are farther apart. Local indicators of SA (LISAs) test the similarity of data clusters. A LISA was calculated for every observation in the dataset, and together with the spatial position and residual of the global model, the data were segmented using two different methods: classification and regression trees (CART) and the multiresolution segmentation algorithm (MS) of the eCognition software. The general model was then re-fitted (localized) to the formed sub-areas. In kriging, the SA is modelled with a variogram, and the spatial correlation is a function of the distance (and direction) between the observation and the point of calculation. A general trend is corrected with the residual information of the neighbourhood, whose size is controlled by the number of the nearest neighbours. Nearness is measured as Euclidian distance. With all methods, the root mean square errors (RMSEs) were lower, but with the methods that segmented the study area, the deviance in single localized RMSEs was wide. Therefore, an element capable of controlling the division or localization should be included in the segmentation-localization process. Kriging, on the other hand, provided stable estimates when the number of neighbours was sufficient (over 30), thus offering the best potential for further studies. Even CART could be combined with kriging or non-parametric methods, such as most similar neighbours (MSN).

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.