432 research outputs found
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Humanist Greek Texts from Finland
No full textThe dataset provides information about the Humanist Greek texts from Finland – mostly from the Royal Academy of Turku (1640–1827) but also containing some "New ancient Greek" poems from the 21st century – displayed in the HUMGRAECA database (https://humgraeca.utlib.ut.ee/), including additional information concerning these texts. The data have been gathered and inserted by Tua Korhonen (with some help by Erkki Sironen) within the framework ”The Humanist Greek Heritage of the Swedish Empire", Swedish Research Council Project number 2016-01881 (PI Johanna Akujärvi, Lund,1.01.2017−31.12.2022, https://projekt.ht.lu.se/helleno-nordica/)
DigiEfekt: digivahendite, õppevara ja sisu kasutamine tundides (use of digital technologies and learning activities in classroom)
No full textREADME-fail (ing k) on leitav DigiEfekti kollektsiooni “Koondfaili” juurest.Digitehnoloogiate, -õppekeskkondade ja -sisu kasutamise andmekogu on osa DigiEfekti (DIGIVARA5) koondandmekogust. Andmekogu koosneb kolmest tabelist, kus on esitatud 3., 6. ja 9. klassi tunnivaatluste ja seotud intervjuude andmed, sh konstruktispetsiifilised tunnused: a) tunniprofiilide andmetabel (“lessonprofiles_data”); b) õpitegevuste vaatluste andmetabel (“learningactivities_data”); c) tundide vaatlus- ja seotud intervjuude andmed digitehnoloogiate, -õppekeskkondade ja -sisu kasutuse osas (“useofdigitaltech_data”). Koodiraamatud on lisatud andmefailidesse teisele lehele ("Codebook"). Lisaks on esitatud eelnevalt kirjeldatud andmetabelite põhjal tehtud analüüside tulemusi ja tausta tutvustavad uuringu raportid: a) tundide õpitegevusi kirjeldav raport (“learningactivities_report_est”) ja b) digitehnoloogiate-, -õppekeskkondade ja -sisu kasutamise raport (“useofdigitaltech_report_est”). Digitehnoloogiate, -õppekeskkondade ja -sisu kasutamise eristamiseks valiti SAMR (substitution, augmentation, modification, redefinition) mudel, mille järgi saab eristada nelja kasutamise dimensiooni: asendamine, täiustamine, modifitseerimine ja ümbermõtestamine (Puentedura, 2006). Õpitegevuste eristamiseks valiti ICAP (interactive, constructive, active, passive) mudel, mille järgi saab kognitiivse kaasatuse alusel eristada nelja dimensiooni õpitegevusi: interaktiivne, konstruktiivne, aktiivne ja passiivne (Chi & Wylie, 2014).[ENG] The use of digital technologies, digital learning environments and digital content in lessons data set is part of the Digiefekt project (DIGIVARA5) aggregated data set. The data set comprises three tables that present the data on the lesson observations in the third, sixth and ninth grades and the data on the related interviews, incl. construct-specific variables: a) the lesson profiles data table (“lessonprofiles_data”), b) observations of learning activities data table (“learningactivities_data”), and c) data on lesson observations and related interviews regarding the use of digital technologies, digital learning environments and digital content (“useofdigitaltech_data”). Codebooks are found in the data files, on the second sheet ("Codebook"). In addition, there are study reports that introduce the results of analyses done based on the above-mentioned data tables and the background: a) report describing the learning activities in lessons (“learningactivities_report_est”) and b) report on the use of digital technologies, digital learning environments and digital content (“useofdigitaltech_report_est”). To differentiate between the uses of digital technologies, digital learning environments and digital content, we opted for the SAMR (Substitution, Augmentation, Modification, Redefinition) model, which differentiates between the aforementioned four dimensions of use (Puentedura, 2006). To differentiate between the learning activities, we chose the ICAP (Interactive, Constructive, Active, Passive) model differentiating between those four dimensions of learning activities based on learners’ cognitive engagement (Chi & Wylie, 2014).Õpitegevuste raporti soovituslik viide eestikeelses allikas: Raave, D. K., Saks, K., Pedaste, M., Heintalu, K., Laanemets, L., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – õpitegevused. Tartu, Tartu Ülikool. http://doi.org/10.23673/re-417Õpitegevuste raporti soovituslik viide ingliskeelses allikas: Raave, D. K., Saks, K., Pedaste, M., Heintalu, K., Laanemets, L., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – õpitegevused. [Rapport of the DigiEfekt project – learning activities]. University of Tartu, Estonia. http://doi.org/10.23673/re-417Digivahendite,-õppevara ja -sisu kasutamise raporti soovituslik viide eestikeelses allikas:
Raave, D. K., Saks, K., Pedaste, M., Heintalu, K., Laanemets, L., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – digivahendite,-õppevara ja - sisu kasutamine. Tartu, Tartu Ülikool. http://doi.org/10.23673/re-417Digivahendite,-õppevara ja -sisu kasutamise raporti soovituslik viide ingliskeelses allikas:
Raave, D. K., Saks, K., Pedaste, M., Heintalu, K., Laanemets, L., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – digivahendite,-õppevara ja - sisu kasutamine. [Rapport of the DigiEfekt project – use of digital technology]. University of Tartu, Estonia. http://doi.org/10.23673/re-41
MetDect WP4: Dataset on the chemical composition of non-ferrous artefacts
No full textThis dataset contains information on the chemical composition of archaeological finds (pXRF data) from Estonia, obtained with the SPECTRO xSORT analyser in August 2022. All analysed finds are stored at the Archaeological Research Collection of Tallinn University. The dataset consists of measurements normalised to 100% and is divided into three sections (silver brooches, pewter objects and copper alloy objects). Tuuli Kurisoo and Ragnar Saage presented the results of the analysis "A pilot study of the workshop areas in Estonia" at the 28th EAA Annual Meeting in Budapest, Hungary, in the session "Metals and metalwork in the Borderlands" on 2 September 2022.
Andmekogu sisaldab Eestist leitud arheoloogiliste leidude keemilise koostise analüüsi (pXRF meetodil), mis mõõdeti 2022. aasta augustis kasutades SPECTRO xSORT instrumenti. Kõik analüüsitud leiud pärinevad Tallinna Ülikooli arheoloogia teaduskogust. Andmekogu sisaldab mõõtmise tulemusi, mis on 100%-ni normaliseeritud. Tuuli Kurisoo ja Ragnar Saage esitasid saadud tulemusi suulise ettekandega “A pilot study of the workshop areas in Estonia” 28. Euroopa arheoloogide assotsiatsiooni aastakonverentsil Budapestis, Ungaris, sessioonil session "Metals and metalwork in the Borderlands" 2. septembril 2022
Bulgaria: Bibliographical database of Bulgarian journalism and media research related to risks and opportunities for deliberative communication (2000–2020)
No full textThe dataset is produced within the framework of the HORIZON 2020 project called MEDIADELCOM (Critical Exploration of Media Related Risks and Opportunities for Deliberative Communication: Development Scenarios of the European Media Landscape) in 2021-2022.
The dataset is one of the 14 single-country data sets included in the consolidated file of country data sets (with 5623 entries), all in msw.xlsx format. All tables are searchable by 20 variables: full reference, year of publication, national/international publication, language, country the publication deals with, time of empirical data gathering, type of publication, open access/not OA, where referenced, focus on journalism domain, focus on media related competences domain, focus on media usage patterns domain, focus on legal and ethical regulations domain, type of the approach, original key words, main topic, comments, country.
As the data has been gathered specifically about the research done in four mentioned domains concerning potential ROs emanating from the news media development for deliberative communication, this database does NOT cover ALL the academic publications in the fields of media and journalism research. Consequently, the above-mentioned conditions limit the generalizations and comparisons based on the current database
DigiEfekt: õpilaste õpipädevus (students’ learning competence)
No full textREADME-fail (ing k) on leitav DigiEfekti kollektsiooni “Koondfaili” juurest.Õpipädevuse andmekogu on osa DigiEfekti (DIGIVARA5) koondandmekogust. Andmekogu koosneb kahest andmetabelist, kus ühes on esitatud 6. ja 9. klassi õpilaste eesti keele, matemaatika ja loodusainete õpipädevuse küsimustike (MSLQ) tulemused (“learningcomp_quest_data”) ning teises 3., 6. ja 9. klassi tundide vaatlusandmed (learningcomp_obs_data). Koodiraamat on andmefailides teisel lehel ("Codebook"). Lisatud on uuringu instrumenti ja tulemusi kirjeldav uuringu raport (“learningcomp_report_est”) ja uuringu instrumendid (“learningcomp_obs_protocol_est” ja “learning_quest_est”).
Õpipädevus on õppija oskus tulla toime erinevates õpisituatsioonides, see on üks olulisemaid eeldusi õpiedu saavutamiseks nii formaalhariduses kui elukestvas õppes. Õpipädevuse all mõistetakse oskust kasutada õpistrateegiaid oma õpitegevuse organiseerimisel, õppematerjali omandamisel ja taasesitamisel.The learning competence data set is part of the Digiefekt project (DIGIVARA5) aggregated data set. The data set comprises two data tables, one of which presents the results of the sixth- and ninth-grade students’ Estonian language, Maths and Science learning competence questionnaires (MSLQ) (“learningcomp_quest_data”) and the other the data on the lesson observations in the third, sixth and ninth grades (learningcomp_obs_data). The codebook is found on the second sheet in the data files ("Codebook"). Also added are the study report describing the study instrument and results (“learningcomp_report_est”) and the study instruments (“learningcomp_obs_protocol_est” and “learning_quest_est”).
Learning competence is the learner’s ability to cope in different learning situations; it is one of the most important prerequisites for achieving academic success in both formal education and lifelong learning. Learning competence refers to one’s ability to use learning strategies in organising one’s learning, acquiring the learning material and reproducing it.Raporti soovituslik viide eestikeelses allikas: Saks, K., Raave, D. K., Heintalu, K., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – õpilaste õpipädevus. Tartu Ülikool. https://datadoi.ee/handle/33/548Raporti soovituslik viide ingliskeelses allikas:
Saks, K., Raave, D. K., Heintalu, K., Remmelg, M., Ilosaar, A., Veskus, K. (2022) DigiEfekti põhiuuringu tulemuste raport – õpilaste õpipädevus. [Report of the DigiEfekt project – students’ learning competence]. University of Tartu. https://datadoi.ee/handle/33/54
Digiefekti projekti koondfail (DigiEfekt project merged data)
No full textDigiEfekti projekti (DIGIVARA5) koondandmekogu koosneb järgmistest osadest: a) koondandmefail (“digiefekt_merged_data”), mis sisaldab konstruktispetsiifilisi tunnuseid ja taustatunnuseid; b) DigiEfekti uuringu lõppraport (“digiefekt_project_final_report_est”); c) hariduslike erivajaduste raport (“edspecialneeds_report_est”); ja d) DigiEfekti projektis kasutatud õpilaste ja lapsevanemate taustaandmete küsimustikud (“background_instrument_est”). Koodiraamat on lisatud andmefaili teisele lehele (“Codebook”).[ENG]
The aggregated data set of the DigiEfekt project (DIGIVARA5) comprises the following parts: a) merged data set (“digiefekt_merged_data”), which contains construct-specific variables and background variables; b) the final report of the Digiefekt study (“digiefekt_project_final_report_est”); c) the special educational needs report (“edspecialneeds_report_est”); and d) students’ and parents’ background data questionnaires used in the Digiefekt project (“background_instrument_est”). The codebook is found on the second sheet of the data file (“Codebook”).DigiEfekti projekti lõppraporti soovituslik viide eestikeelses allikas: Pedaste, M., Raave, D. K., & Baucal, A. (2023) Digitaalsete õppematerjalide kasutamise efekt õpilaste õpitulemustele. Tartu Ülikool. https://datadoi.ee/handle/33/552Raporti soovituslik viide ingliskeelses allikas:
Pedaste, M., Raave, D. K., & Baucal, A. (2023). Digitaalsete õppematerjalide kasutamise efekt õpilaste õpitulemustele [The effect of using digital learning materials on students’ academic outcomes]. University of Tartu. http://doi.org/10.23673/re-41
DigiEfekt: õpilaste digipädevus (digital competence)
No full textREADME-fail (ing k) on leitav DigiEfekti kollektsiooni “Koondfaili” juurest.Digipädevuse andmekogu on osa DigiEfekti (DIGIVARA5) koondandmekogust. Andmekogu koosneb andmetabelist (digicomp_data"), kus on esitatud 3., 6. ja 9. klassi õpilaste sügisese ja kevadise andmekogumise andmed, sh konstruktispetsiifilised tunnused. Koodiraamat on lisatud andmefailidesse teisele lehele ("Codebook"). Lisatud on uuringu instrumenti ja tulemusi kirjeldav raport (“digicomp_report_est”) ning digipädevuse test koos hindamisjuhendiga (digitest_instrument_est).
Digipädevus on üks kaheksast üldpädevusest, mida õppekavaüleselt koolides arendatakse. Digipädevuse hindamiseks oleme koostanud testi, mis avab õpilaste digipädevuse taseme läbi kümne dimensiooni: sotsiaalsed aspektid, tajutud kontroll, käitumuslikud hoiakud, käitumiskavatsus, digimaailmas enese ja teiste kaitsmine, digimaailmas enese ja teiste kaitsmine, digimaailmas seaduslik toimetamine (reeglite tundmine), digimaterjalide loomine, digisisu programmeerimine, digimaailmas suhtlemine, digivahenditega toimingute tegemine. Hilisemad analüüsid on näidanud, et sotsiaalseid aspekte ei ole mõistlik eraldi käsitleda ja seetõttu on edaspidi soovitatav testi kasutada vastavate väideteta (vt Pedaste, Kallas ja Baucal, 2023).ENG:The digital competence data set is part of the Digiefekt project (DIGIVARA5) aggregated data set. The data set comprises a data table (digicomp_data") that presents the third-, sixth- and ninth-grade students’ data from the autumn and spring data collection rounds, incl. the construct-specific variables. The codebook is found on the second sheet of the data files ("Codebook"). There is also the report on the study instrument and results (“digicomp_report_est”) and the digital competence test along with the assessment guidelines (digitest_instrument_est).
Digital competence is one of eight general competences that are in trans-curricular development in schools. To assess digital competence, we have developed a test that reveals students’ digital competence level through ten dimensions: social aspects, perceived control, behavioural attitudes, behavioural intention, protecting oneself and others in the digital world, legal behaviour in the digital world (knowing the rules), creating digital materials, programming digital content, communicating in the digital world, and performing operations with digital tools. Later analyses have shown that social aspects should not be treated separately; therefore, in the future, it is advisable to omit the corresponding statements when using the test (see Pedaste, Kallas, & Baucal, 2023).Raporti soovituslik viide eestikeelses allikas: Kallas, K. & Pedaste, M. (2022). DigiEfekti põhiuuringu tulemuste raport – digipädevus. Tartu Ülikool. http://doi.org/10.23673/re-411Raporti soovituslik viide ingliskeelses allikas: Kallas, K. & Pedaste, M. (2022). DigiEfekti põhiuuringu tulemuste raport – digipädevus. [Report of the DigiEfekt project – digital competence]. University of Tartu. http://doi.org/10.23673/re-41
Data of iron and cobalt phthalocyanine embedded electrospun carbon nanofiber-based catalysts for anion exchange membrane fuel cell cathode
No full textThis dataset contains the data presented in the figures of pulbished paper "Iron and cobalt phthalocyanine embedded electrospun carbon nanofiber-based catalysts for anion exchange membrane fuel cell cathode" Journal of Catalysis 422, 117-130 (https://doi.org/10.1016/j.jcat.2023.04.008). The electrochemical characterisation data, which was measured in University of Tartu Institute of Chemistry, is for Figures 1, 2, 4, 5, 6, 11 and the nomenclature of the catalysts is the same as in the mentioned article
Archaeological and archaeothanatological overview of the individuals at Tamula cemetery
No full textThis dataset represents the Tamula hunter-gatherer burials included in the article "Buried at home? Stable isotope analysis of the late hunter-gatherer cemetery population at Tamula, SE Estonia" by Tõrv and Eriksson (2023, EJA 27,2; 10.3176/arch.2023.2.02). It gives an archaeological and archaeothanatological background to the burials that are analysed for bulk stable isotope values in this article. The full analysis of the Tamula burials is published in Tõrv 2018. TAn overview of the analysed individuals, grave contexts (Jaanits 1957; Tõrv 2015; 2019), and the information about mortuary practices determined by the application of archaeothanatology (Tõrv 2015; 2018) is given. Young child is 1–5 years, older child 6–11 years old and adolescent 12–17 years old; young adult is 18–25 years old, middle adult 26–45 years old and older adult ˃46 years old (after Buikstra & Ubelaker 1994; Scheuer and Black 2000; Gray Jones 2011)
Humanist Greek Texts from Sweden
No full textThe dataset provides information about Humanist Greek texts from Sweden and concerning Swedes from the 16th to the 21st century, displayed in the HUMGRAECA database (https://humgraeca.utlib.ut.ee/), including additional information about these texts. The data have been gathered and inserted by Johanna Akujärvi within the framework of the collaborative project “Helleno-Nordica. The Humanist Greek Heritage of the Swedish Empire”, Swedish Research Council Project number 2016-01881 (PI Johanna Akujärvi, Lund University, 2017-01-01 − 2022-12-31; https://projekt.ht.lu.se/helleno-nordica/)