Objetos de aprendizagem como mediadores para o ensino de história africana e afro-brasileira: um olhar sobre a prática do professor de química
Bibliographic record
Abstract
Relevant aspects discussed in this paper on the use of Information and Communication Technologies (ICT) in school settings, as well as teaching practice in the use of digital tools. Given the diversity of media, in this paper we highlight the main characteristics of learning objects, presenting in detail four instructional materials built by a multidisciplinary team from the Federal University of Uberlndia, during the term of RIVED (Virtual Interactive Education Network) project. Assuming that these textbooks can be used to work Africanities matters relating to the teaching of chemistry in our research, we analyze the strategies developed by three chemistry teachers to use these materials in their classes, the difficulties encountered in this process and present some situations for discussion of topics related to education for ethnic-racial relations in the school environment, particularly in the teaching of chemistry. This study is a qualitative study in which we maintained direct contact with research subjects and used as tools for building data, questionnaires, interviews and participant observation. Data analysis was performed by the discursive textual analysis method, and our results show that the chemistry teachers, who are active in the schools, know, superficially, the existence of Law 10,639 / 03, which has the obligation to teach subjects related History of the African and Afro-Brazilian culture in all levels of education, and they received no training for the fulfillment of the provisions this legislation. In this sense, our results point to the need for training of teachers who are involved in education at all levels as well as the inclusion of disciplines in undergraduate programs that can empower teachers to create strategies and teaching materials involving this thematic. The use of learning objects was observed that one of those involved in the research, presented in total control using this type of teaching tool in their classrooms while some teachers had difficulties in modifying their teaching practices in order to utilize the full potential of this type of learning material. The participation of teachers in the survey served as a time for reflection and learning for them, which were in contact with educational material that presents a proposal different from other materials already used by them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".