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Record W7061149123

Pedagogical Approaches for Encouraging Interaction Awareness and Interactional Competence in University-Level Second Language Learners

2024· dissertation· en· W7061149123 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2024
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsGermanConversation analysisConversationCompetence (human resources)Second-language acquisitionLanguage acquisitionSocial relationSecond languageCommunicative competenceEmpirical research
DOInot available

Abstract

fetched live from OpenAlex

With my dissertation, I show how learning about interactional patterns and organizational features of spoken language can be achieved for undergraduate second and foreign language (L2) learners, supported by empirical data and arguments drawn from previous research in L2 pedagogy and Conversation Analysis-Second Language Acquisition (CA-SLA) for integrating interactional learning materials and tasks into undergraduate L2 classroom curricula. Through my study, I examine and evaluate the implementation of learning tasks and activities involving recordings and written transcripts of naturally occurring interactions in the L2 for undergraduate learners to learn about interaction and language. This examination is conducted using Interaction Analysis as a methodological framework of investigation, specifically using a reworked version of Schermuly and Scholl’s (2012) Discussion Coding System (DSC) for Group Interaction Analysis. In order to theoretically ground my research, I propose the understanding of interaction awareness (IA) as a prerequisite for the development of interactional competence (IC), where IA can be understood as learners’ capacity to become aware of aspects that are at the core of IC, such as organizational features and reoccurring interactional patterns, pragmatic and social implications of interactional and linguistic features, as well as non-verbal and prosodic features that are observable in spoken interaction. The focus of my study then concentrates on interactional tasks and learning materials comprising recordings and written transcripts of naturally occurring interactions in the L2 for undergraduate learners of German as a means of encouraging IA and language awareness (LA) by way of processes involving discovery learning (DL) and social learning. With my analyses and discussions, I examine the ways that the learners’ observations and discoveries about features of interaction and language, posited during the recorded learning sessions comprising the dataset of my study, can be conceptualized as IA. The collaborative discovery and meaning construction work enacted by the learners during the recorded language sessions comprising my study allow for a close, empirical investigation of the learners’ processes and methods of conduct for invoking reflection and negotiating understanding about interactional and linguistic features of the L2 encountered in the learning materials, thereby leading to an awareness of interaction and language that can be inferred through the recorded learner interactions. The conclusions drawn from my study findings indicate that the learners demonstrated LA through their discussions about individual lexical items and grammatical concepts, for example, with considerations about observed variations in verbal production of specific lexical items, as well as systematicities in spoken language production of verb conjugations in the L2. The concept of IA pushes this understanding of LA further by borrowing and incorporating elements from Conversation Analysis (CA), as shown when the learners demonstrated their capacity to consider, reflect, and formulate hypotheses about these discoveries within the specific, socially situated contexts of each of the observed interactions. Adding to this, IA can constitute further considerations about interaction and language, for example, cultural, regional, or pragmatic implications comprising specific instances or variations of language use in spoken interaction, or specific processes relating to certain points in the interaction, for example, becoming aware of linguistic and interactional processes and re-occurring patterns to do with positional features of interaction, such as goodbyes and conversational closing sequences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0020.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.286
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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