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Register a new userTowards Inclusive Practices with Indigenous Knowledge
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Aparna Venkatesan
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Astronomy across world cultures is rooted in Indigenous Knowledge. We share models of partnering with indigenous communities involving Collaboration with Integrity to co-create an inclusive scientific enterprise on Earth and in space.
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We present the second edition of a Best Practices Guide for academic departments and other institutions striving to create more inclusive environments for physicists and astronomers in the LGBT+ community. Our recommendations incorporate new research since the original, 2014 edition, and are designed for anyone who wishes to become aware of -- and help mitigate -- the extra burdens that face members of the LGBT+ community in the physical sciences.
The Multimessenger Diversity Network (MDN), formed in 2018, extends the basic principle of multimessenger astronomy -- that working collaboratively with different approaches enhances understanding and enables previously impossible discoveries -- to equity, diversity, and inclusion (EDI) in science research collaborations. With support from the National Science Foundation INCLUDES program, the MDN focuses on increasing EDI by sharing knowledge, experiences, training, and resources among representatives from multimessenger science collaborations. Representatives to the MDN become engagement leads in their collaboration, extending the reach of the community of practice. An overview of the MDN structure, lessons learned, and how to join are presented.
Since its serendipitous discovery in 1896 by Henry Becquerel, radioactivity has called the attention of both the scientific community and the broad audience due to its intriguing nature, its multiple applications and its controversial uses. For this reason, the teaching of the phenomenon is considered a key ingredient in the path towards developing critical-thinking skills in many secondary science education curricula. Despite being one of the basic concepts in general physics courses, the scientific teaching literature of the last 40 years reports a great deal of misconceptions and conceptual errors related to radioactivity that seemingly appear regardless of the context. This study explores, for the first time, the knowledge status on the topic on a sample of N=191 secondary school students and Y=29 Physics-and-Chemistry trainee teachers in the Spanish region of Valencia. To this aim, a revised version of a diagnostic tool developed by Martins cite{Mar92} has been employed. In general, the results reveal an evolution from a widespread dissenting notion on the phenomenon, which is staunchly related to danger, hazard and destruction in the lowest educational levels, towards a more rational, relative and multidimensional perspective in the highest ones. Furthermore, the great overlap of the ideas, emotions and attitudes of the inquired individuals with the main misconceptions and conceptual mistakes reported in the literature for different educational contexts unveils the urgent need to develop new teaching strategies leading to a meaningful learning of the associated nuclear science concepts.
Knowledge tracing, the act of modeling a students knowledge through learning activities, is an extensively studied problem in the field of computer-aided education. Although models with attention mechanism have outperformed traditional approaches such as Bayesian knowledge tracing and collaborative filtering, they share two limitations. Firstly, the models rely on shallow attention layers and fail to capture complex relations among exercises and responses over time. Secondly, different combinations of queries, keys and values for the self-attention layer for knowledge tracing were not extensively explored. Usual practice of using exercises and interactions (exercise-response pairs) as queries and keys/values respectively lacks empirical support. In this paper, we propose a novel Transformer based model for knowledge tracing, SAINT: Separated Self-AttentIve Neural Knowledge Tracing. SAINT has an encoder-decoder structure where exercise and response embedding sequence separately enter the encoder and the decoder respectively, which allows to stack attention layers multiple times. To the best of our knowledge, this is the first work to suggest an encoder-decoder model for knowledge tracing that applies deep self-attentive layers to exercises and responses separately. The empirical evaluations on a large-scale knowledge tracing dataset show that SAINT achieves the state-of-the-art performance in knowledge tracing with the improvement of AUC by 1.8% compared to the current state-of-the-art models.
As the oldest science common to all human cultures, astronomy has a unique connection to indigenous knowledge (IK) and the long history of indigenous scientific contributions. Many STEM disciplines, agencies and institutions have begun to do the work of recruiting and retaining underrepresented minorities, including indigenous, Native American and Native Hawaiian professionals. However, with the expansion of telescope facilities on sacred tribal or indigenous lands in recent decades, and the current urgency of global crises related to climate, food/water sovereignty and the future of humanity, science and astronomy have the opportunity more than ever to partner with indigenous communities and respect the wealth of sustainable practices and solutions inherently present in IK. We share a number of highly successful current initiatives that point the way to a successful model of collaboration with integrity between western and indigenous scholars. Such models deserve serious consideration for sustained funding at local and institutional levels. We also share six key recommendations for funding agencies that we believe will be important first steps for nonindigenous institutions to fully dialog and partner with indigenous communities and IK to build together towards a more inclusive, sustainable and empowering scientific enterprise.
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