Bibliographic record
Abstract
Qualitative and descriptive research methods have been very common procedures for conducting research in many disciplines, including education, psychology, and social sciences. These types of research have also begun to be increasingly used in the field of second language teaching and learning. The interest in such methods, particularly in qualitative research, is motivated in part by the recognition that L2 teaching and learning is complex. To uncover this complexity, we need to not only examine how learning takes place in general or what factors affect it, but also provide more in-depth examination and understanding of individual learners and their behaviors and experiences. Qualitative and descriptive research is well suited to the study of L2 classroom teaching, where conducting tightly controlled experimental research is hardly possible, and even if controlled experimental research is conducted in such settings, the generalizability of its findings to real classroom contexts are questionable. Therefore, Language Teaching Research receives many manuscripts that report qualitative or descriptive research. The terms qualitative research and descriptive research are sometimes used interchangeably. However, a distinction can be made between the two. One fundamental characteristic of both types of research is that they involve naturalistic data. That is, they attempt to study language learning and teaching in their naturally occurring settings without any intervention or manipulation of variables. Nonetheless, these two types of research may differ in terms of their goal, degree of control, and the way the data are analyzed. The goal of descriptive research is to describe a phenomenon and its characteristics. This research is more concerned with what rather than how or why something has happened. Therefore, observation and survey tools are often used to gather data (Gall, Gall, & Borg, 2007). In such research, the data may be collected qualitatively, but it is often analyzed quantitatively, using frequencies, percentages, averages, or other statistical analyses to determine relationships. Qualitative research, however, is more holistic and often involves a rich collection of data from various sources to gain a deeper understanding of individual participants, including their opinions, perspectives, and attitudes. Qualitative research collects data qualitatively, and the method of analysis is 572747 LTR0010.1177/1362168815572747Language Teaching ResearchEditorial editorial2015
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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 | 0.501 | 0.692 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.012 | 0.021 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".