Facilitating Lexical Acquisition in Beginner Learners of Italian through Popular Song
Bibliographic record
Abstract
This study examines the effects of Song and Involvement Load on the acquisition and retention of lexical items by beginner learners of Italian. Lexical acquisition is investigated via an incidental learning experiment that is based on the premise that growth in L2 vocabulary results from rehearsal and repeated exposure to lexical items in a variety of contexts. More specifically, the study hypothesizes that Song contributes to subvocal rehearsal, a mechanism that facilitates the retention of phonological information. In addition, the study hypothesizes that Involvement Load, as posited by Laufer and Hulstijn (2001), contributes to retention through “elaborate processing”(Craik & Tulving, 1975) of lexical items.\nIn order to evaluate participants‟ lexical acquisition, an experiment with pretest/posttest design was carried out. Participants were divided into one of five groups consisting of a Control Group and four treatment groups. Treatment groups were exposed to a Song either in a sung condition or read as a poem (i.e. without music) while the Control Group completed only the pretest and posttests. Treatment groups also completed lexical tasks designed with either low or high levels of Involvement Load. The pretest and posttests (administered at four and eight weeks respectively after the pretest) were based on Paribakht and Wesche‟s (1996) Vocabulary\niii\nKnowledge Scale. It was hypothesized that in the case of both short-term acquisition (four weeks after the pretest) and retention (eight weeks thereafter) (i) participants exposed to Song would obtain higher scores than participants only exposed to the lyrics; (ii) participants completing High Involvement tasks would score higher than participants completing Low Involvement tasks; and (iii) the effects of Song would be greater than the effects of Involvement Load on test scores.\nResults indicated that at both posttests, participants exposed to Song obtained higher scores than participants only exposed to lyrics (p=0.004). Additionally, participants carrying out High Involvement tasks scored higher than participants carrying out Low Involvement tasks (p=0.017). However, a comparison of the strength of the effects of Song and Involvement Load on acquisition and retention of target items yielded inconclusive results (p=.383).\nThe validation of many of the hypotheses suggests that song and involvement load are effective in the acquisition and retention of L2 lexical items and should be implemented in the L2 curriculum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".