Emotions in a Web-based Learning Environment

The aim of this thesis was to examine emotions in a web-based learning environment (WBLE). Theoretically, the thesis was grounded on the dimensional model of emotions. Four empirical studies were conducted. Study I focused on students’ anxiety and their self-efficacy in computer-using situations. Studies II and III examined the influence of experienced emotions on students’ collaborative visible and non-collaborative invisible activities and lurking in a WBLE. Study II also focused on the antecedents of the emotions students experience in a web-based learning environment. Study IV concentrated on clarifying the differences between emotions experienced in face-to-face and web-based collaborative learning. The results of these studies are reported in four original research articles published in scientific journals. The present studies demonstrate that emotions are important determinants of student behaviour in a web-based learning, and justify the conclusion that interactions on the web can and do have an emotional content. Based on the results of these empirical studies, it can be concluded that the emotions students experience during the web-based learning result mostly from the social interactions rather than from the technological context. The studies indicate that the technology itself is not the only antecedent of students’ emotional reactions in the collaborative web-based learning situations. However, the technology itself also exerted an influence on students’ behaviour. It was found that students’ computer anxiety was associated with their negative expectations of the consequences of using technology-based learning environments in their studies. Moreover, the results also indicated that student behaviours in a WBLE can be divided into three partially overlapping classes: i) collaborative visible ii) non-collaborative invisible activities, and iii) lurking. What is more, students’ emotions experienced during the web-based learning affected how actively they participated in such activities in the environment. Especially lurkers, i.e. students who seldom participated in discussions but frequently visited the online environment, experienced more negatively valenced emotions during the courses than did the other students. This result indicates that such negatively toned emotional experiences can make the lurking individuals less eager to participate in other WBLE courses in the future. Therefore, future research should also focus more precisely on the reasons that cause individuals to lurk in online learning groups, and the development of learning tasks that do not encourage or permit lurking or inactivity. Finally, the results from the study comparing emotional reactions in web-based and face-to-face collaborative learning indicated that the learning by means of web-based communication resulted in more affective reactivity when compared to learning in a face-to-face situation. The results imply that the students in the web-based learning group experienced more intense emotions than the students in the face-to-face learning group.The interpretations of this result are that the lack of means for expressing emotional reactions and perceiving others’ emotions increased the affectivity in the web-based learning groups. Such increased affective reactivity could, for example, debilitate individual’s learning performance, especially in complex learning tasks. Therefore, it is recommended that in the future more studies should be focused on the possibilities to express emotions in a text-based web environment to ensure better means for communicating emotions, and subsequently, possibly decrease the high level of affectivity. However, we do not yet know whether the use of means for communicating emotional expressions via the web (for example, “smileys” or “emoticons”) would be beneficial or disadvantageous in formal learning situations. Therefore, future studies should also focus on assessing how the use of such symbols as a means for expressing emotions in a text-based web environment would affect students’ and teachers’ behaviour and emotional state in web-based learning environments.Siirretty Doriast

Analyzing Temporalities in Parliamentary Speech about Ideologies Using Dependency Parsed Data

Publisher Copyright: © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)The temporal aspects of politics have been discussed extensively by political theorists, but have not been explored using grammatically parsed textual datasets. This paper explores the ways in which future, present and past are projected and referred to in speeches in the Finnish parliament that talk about ideologies. Ideologies are crucial categories of thinking about the political past and future and therefore serve as a case in which temporality is expressed in a variety of ways. We use a dataset drawn from Finnish parliamentary records from 1980 to 2021 and operationalize morpho-syntactic information on clause structures and grammatical tense system to explore the different temporal profiles of ideologies. We show how some isms, like communism and fascism, are much more likely to appear in the context of the past, whereas others, like capitalism and racism, tend to appear in the present tense. We further develop a framework for analyzing temporality based on clause structures and grammatical tense and relate that to how the study of politics has approached time in parliamentary speaking.Peer reviewe

Auditory affective processing requires awareness

Recent work has challenged the previously widely accepted belief that affective processing does not require awareness and can be carried out with more limited resources than semantic processing. This debate has focused exclusively on visual perception, even though evidence from both human and animal studies suggests that existence for nonconscious affective processing would be physiologically more feasible in the auditory system. Here we contrast affective and semantic processing of nonverbal emotional vocalizations under different levels of awareness in three experiments, using explicit (two-alternative forced choice masked affective and semantic categorization tasks, Experiments 1 and 2) and implicit (masked affective and semantic priming, Experiment 3) measures. Identical stimuli and design were used in the semantic and affective tasks. Awareness was manipulated by altering stimulus-mask signal-to-noise ratio during continuous auditory masking. Stimulus awareness was measured on each trial using a four-point perceptual awareness scale. In explicit tasks, neither affective nor semantic categorization could be performed in the complete absence of awareness, while both tasks could be performed above chance level when stimuli were consciously perceived. Semantic categorization was faster than affective evaluation. When the stimuli were partially perceived, semantic categorization accuracy exceeded affective evaluation accuracy. In implicit tasks neither affective nor semantic priming occurred in the complete absence of awareness, whereas both affective and semantic priming emerged when participants were aware of the primes. We conclude that auditory semantic processing is faster than affective processing, and that both affective and semantic auditory processing are dependent on awareness

Nonparametric Exponential Family Graph Embeddings for Multiple Representation Learning

acceptedVersionPeer reviewe

Hierarchical Bayesian aspects of distributed neuromagnetic source models

Magnetoencephalography (MEG) enables noninvasive measurements of cerebral activity with excellent temporal resolution, but localising the neural currents generating the extracranial magnetic fields admits no unique solution. By imposing some mathematical constraints on the currents, reasonable solutions to this electromagnetic inverse problem can be obtained. In this work, we adopt the statistical formulation of the inverse problem in which the constraints are encoded as Bayesian prior probabilities. The prior is combined with a statistical MEG observation model via Bayes' theorem to yield the posterior probability of the unknown parameters, that is the currents, given the MEG data and modeling assumptions. Apart from the currents, the prior probability density may contain further parameters which are subject to uncertainty. These parameters are not related directly to the MEG observations and are called second-level parameters or hyperparameters, giving the model a hierarchical structure. The thesis considers hierarchical generalisations of the classical Minimum-Norm and Minimum-Current Estimates (MNE and MCE). The MNE and MCE are distributed source reconstruction methods from which the former is known to produce spatially diffuse distributions and the latter more focal. The here studied extensions of the MNE and MCE prior structures allow more general and flexible modeling of distributed sources with properties in between MNE and MCE. The first two studies included in this thesis involve more theoretical Bayesian analyses on the properties of the hierarchical distributed source models and the resulting inverse estimates. The latter two studies focus on validation of the models with empirical MEG data, practical analyses and interpretation of the inverse estimates.Magnetoenkefalografia (MEG) mahdollistaa pään ulkopuolelta tapahtuvan aivotoimintojen mittaamisen hyvällä ajallisella tarkkuudella, mutta nämä magneettikentät synnyttävien aivokudoksen sähkövirtojen paikallistaminen vaatii ns. sähkömagneettisen käänteisongelman ratkaisun, joka ei ole yksikäsitteinen. Jos virtakonfiguraatioille asetetaan sopivia matemaattisia rajoitteita, on kuitenkin mahdollista löytää käyttökelpoisia ratkaisuja tähän käänteisongelmaan. Tässä työssä käänteisongelmaa lähestytään tilastollisesti, ja matemaattiset rajoitteet muotoillaan Bayesilaisittain a priori todennäköisyyksinä. Tämä priorijakauma yhdistetään tilastollisen MEG-havaintomallin kanssa, jolloin saadaan Bayesin teoreeman avulla tuntemattomien parametrien eli virtakonfiguraatioiden a posteriori -jakauma, joka kertoo eri virtakonfiguraatioden todennäköisyydet, annettuna havaittu data sekä tehdyt mallioletukset. Virtojen lisäksi priorijakaumaan saattaa liittyä muita tuntemattomia suureita, jotka sisältävät epävarmuutta. Nämä parametrit eivät kytkeydy suoraan MEG-mittauksiin, joten ne ovat siis sähkövirtoihin verrattuna seuraavalla mallitasolla. Näitä priorin parametreja kutsutaan hyperparametreiksi, ja mallilla on hierarkinen rakenne. Väitöskirjassa tutkitaan klassisten miniminormi- ja minimivirtaestimaattien hierarkisia yleistyksiä. Miniminormi- ja minimivirtaestimaatit ovat lähdejakaumamalleihin liittyviä menetelmiä, joista ensimmäinen tuottaa paikallisesti varsin laajalle levineitä ja jälkimmäinen fokaalimpia käänteisongelman ratkaisuja. Näiden menetelmien tässä työssä tutkitut laajennukset mahdollistavat myös yleisempien ja joustavampien, ominaisuuksiltaan miniminormi- ja minimivirtaoletusten väliin sijoittuvien lähdejakaumien mallintamisen. Kaksi ensimmäistä osatyötä keskittyvät esitettyjen hierarkisten Bayesilaisten lähdejakaumamallien sekä niiden tuottamien käänteisongelman ratkaisujen teoreettiseen tutkimiseen. Kahdessa jälkimmäisessä osatyössä pyritään validoimaan menetelmät käyttäen mitattua MEG dataa, sekä selventämään näiden hierarkisten käänteisongelman ratkaisujen käytännön merkitystä ja tulkintaa.reviewe

Mistä puhumme kun puhumme tunteista?

Suomen kielen sana tunne on monimerkityksinen. Se viittaa paitsi fysiologiseen tunnereaktioon, myös tuntoaistin toimintaan sekä mielensisäisiin, tietoisiin kokemuksiin ja tuntemuksiin. Viimeksi kuluneen sadan vuoden aikana käsitys tunteiden toiminnasta on muuttunut radikaalisti

Data-driven approaches in the investigation of social perception

The complexity of social perception poses a challenge to traditional approaches to understand its psychological and neurobiological underpinnings. Data-driven methods are particularly well suited to tackling the often high-dimensional nature of stimulus spaces and of neural representations that characterize social perception. Such methods are more exploratory, capitalize on rich and large datasets, and attempt to discover patterns often without strict hypothesis testing. We present four case studies here: behavioural studies on face judgements, two neuroimaging studies of movies, and eyetracking studies in autism. We conclude with suggestions for particular topics that seem ripe for data-driven approaches, as well as caveats and limitations

Using parsed and annotated corpora to analyze parliamentarians' talk in Finland

We present a search system for grammatically analyzed corpora of Finnish parliamentary records and interviews with former parliamentarians, annotated with metadata of talk structure and involved parliamentarians, and discuss their use through carefully chosen digital humanities case studies. We first introduce the construction, contents, and principles of use of the corpora. Then we discuss the application of the search system and the corpora to study how politicians talk about power, how ideological terms are used in political speech, and how to identify narratives in the data. All case studies stem from questions in the humanities and the social sciences, but rely on the grammatically parsed corpora in both identifying and quantifying passages of interest. Finally, the paper discusses the role of natural language processing methods for questions in the (digital) humanities. It makes the claim that a digital humanities inquiry of parliamentary speech and interviews with politicians cannot only rely on computational humanities modeling, but needs to accommodate a range of perspectives starting with simple searches, quantitative exploration, and ending with modeling. Furthermore, the digital humanities need a more thorough discussion about how the utilization of tools from information science and technologies alter the research questions posed in the humanities.Peer reviewe

Effects of conversation content on viewing dyadic conversations

People typically follow conversations closely with their gaze. We asked whether this viewing is influenced by what is actually said in the conversation and by the viewer’s psychological condition. We recorded the eye movements of healthy (N = 16) and depressed (N = 25) participants while they were viewing video clips. Each video showed two people, each speaking one line of dialogue about socio-emotionally important (i.e., personal) or unimportant topics (matter-of-fact). Between the spoken lines, the viewers made more saccadic shifts between the discussants, and looked more at the second speaker, in personal vs. matter-of-fact conversations. Higher depression scores were correlated with less looking at the currently speaking discussant. We conclude that subtle social attention dynamics can be detected from eye movements and that these dynamics are sensitive to the observer’s psychological condition, such as depression