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Journal articles on the topic 'Dataâdriven instruction'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Smart, Jonathan. "The role of guided induction in paper-based data-driven learning." ReCALL 26, no. 2 (2014): 184–201. http://dx.doi.org/10.1017/s0958344014000081.

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AbstractThis study examines the role of guided induction as an instructional approach in paper-based data-driven learning (DDL) in the context of an ESL grammar course during an intensive English program at an American public university. Specifically, it examines whether corpus-informed grammar instruction is more effective through inductive, data-driven learning or through traditional deductive instruction. In the study, 49 participants completed two weeks of ESL grammar instruction on the passive voice in English. The learners participated in one of three instructional treatments: a data-dri

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Bertrand, Melanie, and Julie Marsh. "How data-driven reform can drive deficit thinking." Phi Delta Kappan 102, no. 8 (2021): 35–39. http://dx.doi.org/10.1177/00317217211013936.

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Propelled by accountability policies, leaders have touted data-driven decision making as a means to improve K-12 student outcomes and drive equity, as teachers analyze data to change instruction. However, many data-driven decision-making reforms have failed to challenge inequity. Melanie Bertrand and Julie Marsh’s study of six middle schools shows that teachers’ deficit thinking about emergent bilingual students, students with disabilities, and “struggling” students contributes to this failure of data reforms. They argue that blaming these groups for test scores ultimately works to uphold syst

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Wieman, Rob. "Data Do Not Drive Themselves." Mathematics Teacher 111, no. 7 (2018): 535–39. http://dx.doi.org/10.5951/mathteacher.111.7.0535.

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Several years ago, I was working with a group of high school math teachers. Their assistant principal was impressed with their practice of sharing data from common assessments, assuming that they used these data to drive instruction. However, when I asked the teachers which data they used when teaching, they said that student work and questions during class were much more valuable. Apparently, people may interpret “data-driven instruction” differently. As a mathematics teacher, what data can you collect, and how can you use those data to improve instruction?

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Douglas, Michael. "Data-Driven Instruction Improves Spoken Language Skills." Hearing Journal 69, no. 7 (2016): 12. http://dx.doi.org/10.1097/01.hj.0000489194.84927.57.

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Dudek, Christopher M., Linda A. Reddy, Adam Lekwa, Anh N. Hua, and Gregory A. Fabiano. "Improving Universal Classroom Practices Through Teacher Formative Assessment and Coaching." Assessment for Effective Intervention 44, no. 2 (2018): 81–94. http://dx.doi.org/10.1177/1534508418772919.

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This article presents the Classroom Strategies Coaching (CSC) Model, a data-driven coaching approach that uses teacher formative assessment data to drive improvements in universal practices. The classroom strategies assessment system (CSAS), a formative assessment of evidence-based instructional and behavioral management practices was used to facilitate the coaching process. Results from 32 elementary school teachers who received brief coaching after participating as waitlist controls in a randomized controlled trial are presented. Teachers’ practices remained stable across baseline periods. F

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Klas, W., U. Westermann, T. Rose, et al. "The CardioOP-Data Clas (CDC)." Methods of Information in Medicine 42, no. 01 (2003): 68–78. http://dx.doi.org/10.1055/s-0038-1634211.

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Summary Objectives: Self-directed and customized medical education programs are gaining importance in health care instruction. We prototypically implemented a repository-driven online computer system (CardioOP) for teleteaching in Heart Surgery. It supports authoring and multiple re-use of multimedia data for different user groups in different instructional applications and therefore requires a process of content management. Methods: We defined objectives for a terminological system to support semantic, cross-media type annotation and retrieval of learning objects: domain completeness, German

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Wyse, Sara A., Tammy M. Long, and Diane Ebert-May. "Teaching Assistant Professional Development in Biology: Designed for and Driven by Multidimensional Data." CBE—Life Sciences Education 13, no. 2 (2014): 212–23. http://dx.doi.org/10.1187/cbe.13-06-0106.

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Graduate teaching assistants (TAs) are increasingly responsible for instruction in undergraduate science, technology, engineering, and mathematics (STEM) courses. Various professional development (PD) programs have been developed and implemented to prepare TAs for this role, but data about effectiveness are lacking and are derived almost exclusively from self-reported surveys. In this study, we describe the design of a reformed PD (RPD) model and apply Kirkpatrick's Evaluation Framework to evaluate multiple outcomes of TA PD before, during, and after implementing RPD. This framework allows eva

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MUDRAYA, O. V. "Need for data-driven instruction of engineering English." IEEE Transactions on Professional Communication 47, no. 1 (2004): 65–70. http://dx.doi.org/10.1109/tpc.2004.824296.

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Li, Qiong. "L2 Chinese learners’ pragmatic developmental patterns in data-driven instruction and computer-mediated communication (CMC)." Applied Pragmatics 1, no. 2 (2019): 154–83. http://dx.doi.org/10.1075/ap.19006.li.

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Abstract This study examined second language (L2) Chinese learners’ developmental patterns of pragmatic competence in two computer-mediated communication (CMC) conditions: (1) CMC with data-driven instruction embedded in the course of CMC and (2) CMC without data-driven instruction. Learners’ pragmatic competence was operationalized as their ability to use a Chinese sentence final particle (SFP) ne during CMC with a native speaker partner. The study investigated: (1) whether learners (as a group) developed their use of ne over time in the two CMC conditions, and (2) how individual learners cha

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Li, Qiao, Ping Wang, Yifan Sun, Yinglong Zhang, and Chuanfu Chen. "Data-driven decision making in graduate students’ research topic selection." Aslib Journal of Information Management 71, no. 5 (2019): 657–76. http://dx.doi.org/10.1108/ajim-01-2019-0019.

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Purpose With the advent of the intelligent environment, as novice researchers, graduate students face digital challenges in their research topic selection (RTS). The purpose of this paper is to explore their cognitive processes during data-driven decision making (DDDM) in RTS, thus developing technical and instructional strategies to facilitate their research tasks. Design/methodology/approach This study developes a theoretical model that considers data-driven RTS as a second-order factor comprising both rational and experiential modes. Additionally, data literacy and visual data presentation

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Halverson, Richard, Jeffrey Grigg, Reid Prichett, and Chris Thomas. "The New Instructional Leadership: Creating Data-Driven Instructional Systems in School." Journal of School Leadership 17, no. 2 (2007): 159–94. http://dx.doi.org/10.1177/105268460701700202.

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Harshman, Jordan, and Ellen Yezierski. "Guiding teaching with assessments: high school chemistry teachers’ use of data-driven inquiry." Chemistry Education Research and Practice 16, no. 1 (2015): 93–103. http://dx.doi.org/10.1039/c4rp00188e.

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Data-driven inquiry (DDI) is the process by which teachers design and implement classroom assessments and use student results to inform/adjust teaching. Although much has been written about DDI, few details exist about how teachers conduct this process on a day-to-day basis in any specific subject area, let alone chemistry. Nineteen high school chemistry teachers participated in semi-structured interviews regarding how they used assessments to inform teaching. Results are reported for each step in the DDI process. Goals – there was a lack in specificity of learning and instructional goals and

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Azaria, Helnye, and Yosi Veler. "Machine instructions of a data-driven architecture — Design considerations." Microprocessing and Microprogramming 20, no. 1-3 (1987): 99–105. http://dx.doi.org/10.1016/0165-6074(87)90126-8.

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Marsh, Julie A., Jennifer Sloan McCombs, and Francisco Martorell. "How Instructional Coaches Support Data-Driven Decision Making." Educational Policy 24, no. 6 (2009): 872–907. http://dx.doi.org/10.1177/0895904809341467.

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Garstki, Kevin James, Chris Larkee, and John LaDisa. "A Role for Immersive Visualization Experiences in Teaching Archaeology." Studies in Digital Heritage 3, no. 1 (2019): 46–59. http://dx.doi.org/10.14434/sdh.v3i1.25145.

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As archaeologists continue to utilize digital 3D visualization technologies, instruction can also benefit from purpose-driven uses of these data. This paper outlines a pilot project that used previously captured 3D data in a large-scale immersive environment to supplement the instruction of basic archaeological concepts to an undergraduate introductory anthropology class. The flexibility of the platform allowed excavation trenches to be investigated in three-dimensions, enhancing the understanding of excavation methods and providing additional insight in the choices of the excavators. Addition

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Darling-Aduana, Jennifer. "A Remote Instructor Like Me: Student–Teacher Congruence in Online, High School Courses." AERA Open 7 (January 2021): 233285842110187. http://dx.doi.org/10.1177/23328584211018719.

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Students belonging to marginalized groups experience positive impacts when taught by a teacher of the same race, ethnicity, and gender. The unique nature of standardized, asynchronous online course taking allows for greater separation of any possible educational benefits of student versus teacher-driven mechanisms contributing to these improved outcomes. Using a student-by-course fixed effect strategy on data from a large urban school district, I examined associations between whether students experienced racial/ethnic or gender congruence with their remote instructor and both engagement and le

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Rangnes, Hege, and Aslaug Fodstad Gourvennec. "Læreres samtale om pedagogisk bruk av flerspråklige elevers prøveresultater." Acta Didactica Norge 12, no. 4 (2018): 6. http://dx.doi.org/10.5617/adno.6282.

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Siden begynnelsen av 2000-tallet har det vært et utdanningspolitisk ønske i Norge om å kvalitetsvurdere opplæringen i skolen, og det er i den forbindelse innført obligatoriske kartleggingsprøver og nasjonale prøver. Vi vet at lærere er usikre på oppfølgingen av prøveresultatene. Som et ledd i å styrke underveisvurderingen, har Utdanningsdirektoratet lansert digitale læringsstøttende prøver med veiledninger for mellomtrinnet. En av disse prøvene, en vokabularprøve, er særlig innrettet mot den konkrete oppfølgingen av flerspråklige elever. I denne studien undersøker vi, inspirert av et kritisk c

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Bartlett, Dana, Michael Vinella, and Sunddip Panesar-Aguilar. "How Benchmark Is Used in Third Grade Reading Instruction." Education, Language and Sociology Research 2, no. 1 (2021): p85. http://dx.doi.org/10.22158/elsr.v2n1p85.

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Third grade reading teachers at the local setting are not consistently using formative benchmark data to improve student reading performance, creating a gap in practice. This gap in practice may be due to teachers’ lack of capacity to use the data to make changes to their instructional practices. The purpose of this qualitative study was to explore how third grade reading teachers are using data from reading benchmark assessments to improve student reading performance. This research study was guided by two Research Questions (RQs). RQ 1 addressed how third grade teachers are using reading benc

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Heil, Leila. "Synergy in the composition classroom: Powerful learning through technology and instructional design." Journal of Music, Technology & Education 12, no. 2 (2019): 165–78. http://dx.doi.org/10.1386/jmte_00004_1.

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To provide insight into structural, technological and environmental factors that contribute to powerful learning experiences in composition tasks, this instrumental case study offers an examination of the interactions of various elements evident in a music composition class. Data were collected via classroom observations, participant interviews and miscellaneous documents. The synergistic relationship between instructional design components and classroom supports, mediated through the use of technology, served to transform the human–computer interface from problem-solving to possibility-driven

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LoPresto, Michael C., and Timothy F. Slater. "A New Comparison Of Active Learning Strategies To Traditional Lectures For Teaching College Astronomy." Journal of Astronomy & Earth Sciences Education (JAESE) 3, no. 1 (2016): 59. http://dx.doi.org/10.19030/jaese.v3i1.9685.

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Although traditional lectures are still the dominant form of undergraduate instruction, there have been relatively few studies comparing various learner-centered and active learning teaching strategies to one another in order to guide professors in making informed instructional decisions. To study the impact of different active learning approaches, pre-test to posttest learning gains for students receiving instruction on introductory astronomy solar system topics through a combination of collaborative learning activities and formative assessment-driven activities were compared to the gains of

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Eymur, Guluzar. "The influence of the explicit nature of science instruction embedded in the Argument-Driven Inquiry method in chemistry laboratories on high school students’ conceptions about the nature of science." Chemistry Education Research and Practice 20, no. 1 (2019): 17–29. http://dx.doi.org/10.1039/c8rp00135a.

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The aim of the present study was to investigate the influence of the explicit nature of science instruction embedded in the Argument-Driven Inquiry method compared with an implicit inquiry method on eleventh-grade students’ conceptions of NOS. The study used a pre-/post-test control group design to investigate the influence of the explicit nature of science instruction embedded in the Argument-Driven Inquiry method on eleventh grade students’ understanding of NOS. The qualitative method was used to identify the students’ views of NOS. The study involved 45 students (grade 11) enrolled in a che

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Bolgün, M. Ali. "The Significance of Data-driven Descriptions of Forms in Explicit Grammar Instruction." Procedia - Social and Behavioral Sciences 70 (January 2013): 430–46. http://dx.doi.org/10.1016/j.sbspro.2013.01.081.

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Abbott, Mary, Jane Atwater, Younwoo Lee, and Liesl Edwards. "A Data-Driven Preschool PD Model for Literacy and Oral Language Instruction." NHSA Dialog 14, no. 4 (2011): 229–45. http://dx.doi.org/10.1080/15240754.2011.613126.

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Pagoto, Sherry, Kathrine A. Lewis, Laurie Groshon, et al. "STEM undergraduates’ perspectives of instructor and university responses to the COVID-19 pandemic in Spring 2020." PLOS ONE 16, no. 8 (2021): e0256213. http://dx.doi.org/10.1371/journal.pone.0256213.

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Objectives We examined undergraduate STEM students’ experiences during Spring 2020 when universities switched to remote instruction due to the COVID-19 pandemic. Specifically, we sought to understand actions by universities and instructors that students found effective or ineffective, as well as instructor behaviors that conveyed a sense of caring or not caring about their students’ success. Methods In July 2020 we conducted 16 focus groups with STEM undergraduate students enrolled in US colleges and universities (N = 59). Focus groups were stratified by gender, race/ethnicity, and socioeconom

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Moon, Soyeon, and Sun-Young Oh. "Unlearning overgenerated be through data-driven learning in the secondary EFL classroom." ReCALL 30, no. 1 (2017): 48–67. http://dx.doi.org/10.1017/s0958344017000246.

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AbstractThis paper reports on the cognitive and affective benefits of data-driven learning (DDL), in which Korean EFL learners at the secondary level notice and unlearn their “overgenerated be” by comparing native English-speaker and learner corpora with guided induction. To select the target language item and compile learner-corpus-based materials, writing samples of 285 learners were collected. The participants were randomly divided into traditional grammar learning and DDL groups. After providing instruction for each group, one immediate and one delayed writing sessions were implemented. Re

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Catalano, Michelle Malizia, Porcia Vaughn, and Joshua Been. "Using Maps to Promote Data-Driven Decision-Making: One Library’s Experience in Data Visualization Instruction." Medical Reference Services Quarterly 36, no. 4 (2017): 415–22. http://dx.doi.org/10.1080/02763869.2017.1369292.

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Fryer, Roland G. "Injecting Charter School Best Practices into Traditional Public Schools: Evidence from Field Experiments *." Quarterly Journal of Economics 129, no. 3 (2014): 1355–407. http://dx.doi.org/10.1093/qje/qju011.

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Abstract This study examines the impact on student achievement of implementing a bundle of best practices from high-performing charter schools into low-performing, traditional public schools in Houston, Texas, using a school-level randomized field experiment and quasi-experimental comparisons. The five practices in the bundle are increased instructional time, more effective teachers and administrators, high-dosage tutoring, data-driven instruction, and a culture of high expectations. The findings show that injecting best practices from charter schools into traditional Houston public schools si

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Hanowski, Richard J., Robert J. Carroll, Walter W. Wierwille, and Rebecca L. Olson. "Light Vehicle-Heavy Vehicle Interactions: A Preliminary Assessment Using Critical Incident Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 22 (2002): 1844–47. http://dx.doi.org/10.1177/154193120204602214.

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Two recently completed on-road in situ data collection efforts, one involving local/short haul trucking and the other long-haul trucking, provided a large data set in which to conduct an examination of critical incidents (crashes and near-crashes) that occurred between light vehicles and heavy vehicles. Video and non-video data collected during the two studies were used to characterize critical incidents that were recorded between light vehicle and heavy vehicle drivers. Across both studies, 210 light vehicle-heavy vehicle (LV-HV) critical incidents were recorded. Of these, 78 percent were ini

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Park, Vicki, and Amanda Datnow. "Ability Grouping and Differentiated Instruction in an Era of Data-Driven Decision Making." American Journal of Education 123, no. 2 (2017): 281–306. http://dx.doi.org/10.1086/689930.

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Abbott, Mary, Constance Beecher, Sarah Petersen, Charles R. Greenwood, and Jane Atwater. "A Team Approach to Data-Driven Decision-Making Literacy Instruction in Preschool Classrooms." Young Exceptional Children 20, no. 3 (2015): 117–32. http://dx.doi.org/10.1177/1096250615602297.

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Borrero, Noah. "The Real Importance of Student Data: Urban Teachers Using Data to Drive Their Instruction." Curriculum and Teaching 24, no. 1 (2009): 5–14. http://dx.doi.org/10.7459/ct/24.1.02.

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Bouabida, Nihal. "The Effect of Data-driven Learning & Image-schema-based Polysemy Networks Instruction on Learning Spatial Prepositions of Verticality: The Case of Moroccan EFL Learners." JURNAL ARBITRER 7, no. 1 (2020): 62. http://dx.doi.org/10.25077/ar.7.1.62-70.2020.

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This paper reports on a quasi-experimental study investigating the effects of a teaching methodology that combines Cognitive Linguistics (CL) and Corpus Linguistics (CrpL) insights on the acquisition of the two sets of English spatial prepositions of verticality, over/above and under/below. In addition, it is also concerned with learners’ attitudes towards the method of instruction. A total of 55 Moroccan first-year university students participated in this study, 22 of which were assigned to the experimental group, and 26 to the control group. The experimental group received what we termed the

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Men, Haiyan. "Data-Driven Learning in Enhancing Learners’ Language Idiomaticity." International Journal of Emerging Technologies in Learning (iJET) 15, no. 23 (2020): 27. http://dx.doi.org/10.3991/ijet.v15i23.19023.

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As data-driven learning has been advancing across new frontiers in recent years, there is still a paucity of studies on data-driven vocabulary learning model that brings about effectiveness in teaching and learning practices. Idiomaticity, which serves as an important indicator for language proficiency, needs abundant contextualized language input for the acquisition of target words. In this regard, the present study explores whether computer-assisted language learning is effective in vocabulary acquisition, and in the differentiation of synonymous words on the part of learners. Pre-/posttests

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Odom, Arthur Louis, and Clare Valerie Bell. "Developing PK-12 Preservice Teachers' Skills for Understanding Data-Driven Instruction Through Inquiry Learning." Journal of Statistics Education 25, no. 1 (2017): 29–37. http://dx.doi.org/10.1080/10691898.2017.1288557.

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Glover, Todd A., Linda A. Reddy, Alexander Kurz, and Stephen N. Elliott. "Use of an Online Platform to Facilitate and Investigate Data-Driven Instructional Coaching." Assessment for Effective Intervention 44, no. 2 (2018): 95–103. http://dx.doi.org/10.1177/1534508418811593.

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This article presents theoretical and empirical support for a data-driven instructional coaching approach and emerging evidence for the contributions of an online platform in operationalizing, assessing, and facilitating the implementation of key coaching actions for both research and practice. The contributions of an online platform in guiding the implementation and investigation of key coaching actions (i.e., modeling, facilitation of practice, and feedback) throughout a five-phase coaching sequence are presented. The article outlines initial research to demonstrate the utility of the online

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Zhang, Ying. "Combining computer-mediated communication with data-driven instruction: EFL learners’ pragmatic development of compliment responses." System 103 (December 2021): 102624. http://dx.doi.org/10.1016/j.system.2021.102624.

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Havelková, Lenka, and Martin Hanus. "Research into map-analysis strategies: theory- and data-driven approaches." Geografie 124, no. 2 (2019): 187–216. http://dx.doi.org/10.37040/geografie2019124020187.

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This study focuses on the strategies used during an analysis of four types of thematic maps (line symbols, area-shading, choropleths, and diagram maps) on the basis of the use of eyetracking technology. Moreover, it discusses the use of data-driven (spatial and spatiotemporal) and theory-driven (spatiotemporal) methodological approaches to research on the topic and aims to verify their applicability experimentally. The results of the experiment assist in identifying the main merits and limits of these approaches and serve to supplement and expand the results of prior studies. It is apparent th

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Cotos, Elena. "Enhancing writing pedagogy with learner corpus data." ReCALL 26, no. 2 (2014): 202–24. http://dx.doi.org/10.1017/s0958344014000019.

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AbstractLearner corpora have become prominent in language teaching and learning, enhancing data-driven learning (DDL) pedagogy by promoting ‘learning driven data’ in the classroom. This study explores the potential of a local learner corpus by investigating the effects of two types of DDL activities, one relying on a native-speaker corpus (NSC) and the second combining native-speaker and learner corpora. Both types of activities aimed at improving second language writers’ knowledge of linking adverbials and were based on a preliminary analysis of adverbial use in the local learner corpus produ

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Bicehouse, Vaughn, and Jean Faieta. "IDEA At Age Forty: Weathering Common Core Standards And Data Driven Decision Making." Contemporary Issues in Education Research (CIER) 10, no. 1 (2016): 33–44. http://dx.doi.org/10.19030/cier.v10i1.9878.

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Special education, a discipline that aims to provide specialized instruction to meet the unique needs of each child with a disability, has turned 40 years old in the United States. Ever since the passage of the Education for All Handicapped Children Act (P.L. 94-142) in 1975, every state has been directed to provide a free and appropriate education for all students with disabilities (Gallagher, 2000; Rothstein, 1995). The focus of this paper is to revisit the foundations of the special education movement in the United States to show how special education has progressed since 1975. The current

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TANAKA, Takahiro, Kazuhiro FUJIKAKE, Takashi YONEKAWA, et al. "Study on Driver Agent Based on Analysis of Driving Instruction Data — Driver Agent for Encouraging Safe Driving Behavior (1) —." IEICE Transactions on Information and Systems E101.D, no. 5 (2018): 1401–9. http://dx.doi.org/10.1587/transinf.2017edp7203.

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Heredia, Juan, Christian Schlette, and Mikkel Baun Kjaergaard. "Data-Driven Energy Estimation of Individual Instructions in User-Defined Robot Programs for Collaborative Robots." IEEE Robotics and Automation Letters 6, no. 4 (2021): 6836–43. http://dx.doi.org/10.1109/lra.2021.3094781.

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L'Allier, Susan K. "Lessons Learned From Research About Informal Reading Inventories: Keys to Data-Driven Instructional Recommendations." Reading & Writing Quarterly 29, no. 3 (2013): 288–307. http://dx.doi.org/10.1080/10573569.2013.789780.

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Jiang, Shixiao W., and John Harlim. "Parameter Estimation with Data-Driven Nonparametric Likelihood Functions." Entropy 21, no. 6 (2019): 559. http://dx.doi.org/10.3390/e21060559.

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In this paper, we consider a surrogate modeling approach using a data-driven nonparametric likelihood function constructed on a manifold on which the data lie (or to which they are close). The proposed method represents the likelihood function using a spectral expansion formulation known as the kernel embedding of the conditional distribution. To respect the geometry of the data, we employ this spectral expansion using a set of data-driven basis functions obtained from the diffusion maps algorithm. The theoretical error estimate suggests that the error bound of the approximate data-driven like

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Mikulecky, Larry, and Paul Lloyd. "Evaluation of Workplace Literacy Programs: A Profile of Effective Instructional Practices." Journal of Literacy Research 29, no. 4 (1997): 555–85. http://dx.doi.org/10.1080/10862969709547974.

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This study introduces and examines a model for evaluating workplace literacy programs by assessing the impact of workplace literacy instruction in a variety of settings. The model was developed in reaction to the particular assessment difficulties associated with workplace literacy programs to address 2 questions: (a) Are learners in workplace literacy classes able to demonstrate gains between premeasures and postmeasures in areas related to literacy practices? (b) For gains to occur, how much of several instructional practices (e.g., reading/writing practice, use of workplace examples, etc.)

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Little, Michael Harris, Lora Cohen-Vogel, James Sadler, and Becca Merrill. "Data-driven decision making in early education: Evidence From North Carolina’s Pre-K program." education policy analysis archives 27 (March 4, 2019): 18. http://dx.doi.org/10.14507/epaa.27.4198.

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The purpose of this study is to shed light on the use of data in early education settings—specifically, North Carolina’s Pre-K program. In this mixed-methods study, we draw upon in-depth interviews and survey data to examine (1) the types of data available to educators in Pre-K, (2) the ways in which data are intended to be used, (3) how data are reportedly used, and (4) the facilitators and inhibitors of effective data-driven decision making. Our findings reveal that Pre-K settings are data-rich environments, often with informal data collected through developmental screening tools and formati

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Lee, Seungjoon, Felix Dietrich, George E. Karniadakis, and Ioannis G. Kevrekidis. "Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion." Interface Focus 9, no. 3 (2019): 20180083. http://dx.doi.org/10.1098/rsfs.2018.0083.

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In statistical modelling with Gaussian process regression, it has been shown that combining (few) high-fidelity data with (many) low-fidelity data can enhance prediction accuracy, compared to prediction based on the few high-fidelity data only. Such information fusion techniques for multi-fidelity data commonly approach the high-fidelity model f h ( t ) as a function of two variables ( t , s ), and then use f l ( t ) as the s data. More generally, the high-fidelity model can be written as a function of several variables ( t , s 1 , s 2 ….); the low-fidelity model f l and, say, some of its deri

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Kleanthous, Irene, and Maria Meletiou-Mavrotheris. "Early Statistical Reasoning." International Journal of Information Communication Technologies and Human Development 8, no. 1 (2016): 26–41. http://dx.doi.org/10.4018/ijicthd.2016010102.

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This paper explores the potential of dynamic statistics software for supporting the early teaching and learning of statistical and probabilistic concepts integrated within the mathematics curriculum. It shares the experiences from a case study that implemented a data-driven approach to mathematics instruction using the dynamic data-visualization software InspireData©, an educational package specifically designed to meet the learning needs of students in the middle and high school grades (Grades 4-12). The authors report on how a group of fourteen (n=14) Grade 4 (about 9-year-old) students used

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Bao, Kai. "Should We Use It in Our Classrooms: An Analysis of Data-Driven Learning Research." English Linguistics Research 10, no. 3 (2021): 66. http://dx.doi.org/10.5430/elr.v10n3p66.

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Corpus linguistics has become increasingly important to both language researchers and teachers over the past three decades. As a popular practice of corpus linguistics, Data-Driven Learning (DDL) sees a rapidly growing body of research as well as instruction in the field. There is, however, a lack of comprehensive literature reviews that summarize the effectiveness, learners’ perception, as well as factors affecting the success of DDL to guide its practices. In response, this study analyzes previous DDL research to show the feasibility of the activities in EFL classrooms. For the purpose, we c

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Gurusinghe, Gemunu Senadeera, Takashi Nakatsuji, Yoichi Azuta, Prakash Ranjitkar, and Yordphol Tanaboriboon. "Multiple Car-Following Data with Real-Time Kinematic Global Positioning System." Transportation Research Record: Journal of the Transportation Research Board 1802, no. 1 (2002): 166–80. http://dx.doi.org/10.3141/1802-19.

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The real-time kinematic differential Global Positioning System (GPS) has facilitated a new horizon in traffic engineering. Multiple car-following experiments conducted with a real-time kinematic GPS with 10 vehicles participating in a probing field gave high-quality results in headway, speed, relative speed, and acceleration. The expected accuracies for measuring position and speed were 10 mm and 0.16 km/h, respectively. The vehicles were driven in a loop consisting of two parallel straight sections connected by two semicircular curves. Different driving conditions were induced in the platoon

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Sanchez, Christopher A., Benjamin L. Ruddell, Roy Schiesser, and Venkatesh Merwade. "Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities." Hydrology and Earth System Sciences 20, no. 3 (2016): 1289–99. http://dx.doi.org/10.5194/hess-20-1289-2016.

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Abstract. Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data-driven simulation lab exercise that was contextualized within a real-world

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