Depicting Epistemological Obstacles in Understanding the Concept of Sequence and Series
Bibliographic record
Abstract
This study aimed to discover epistemological obstacle on secondary students to solve sequence and series problems based on three indicators, there are a conceptual obstacle, procedural obstacle, and operational technique obstacle. This study was descriptive with qualitative research approaches. Data were collected with the test and interview method. The subjects in this study are students of SMP Negeri 86 Jakarta class VIII based on the errors seen from the diagnostic tests that had been tested. The analysis was done by giving written tests which are essay and interview formatted. Results on analysis showed that: (1) Conceptual obstacle, obstacle that was experienced by students are: students considered that a pattern was said as a numeral pattern because they own odd numeral pattern and own 2,2,2 of difference; were not able to find exact pattern within the problem; considering that Fibonacci numeral sequence was a pattern that form prime numeral pattern; were not able to differ the concept of arithmetics and geometry sequence; were not able to understand the concept of first quarter on arithmetics sequence; error when interpreted the meaning of problems; were not able to intepret what was given on mathematics model; interpreting sum of the first 20 quarters with sequences which own the 20th quarter; and interpreting sum of the first 20 quarters with the 20th quarter; (2) While on procedural obstacle, obstacle that was experienced are: interpreting numeral pattern if they own their pair; error on determining multiplication or difference; and applying formulas incorrectly; (3) Last on operasional technique obstacle, obstacle that was experienced are error on calculation and using sign and symbol mathematics incorrectly.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".