LEADER 03731nam 2200649 a 450 001 9910791225803321 005 20200520144314.0 010 $a1-00-344368-0 010 $a1-000-97990-3 010 $a1-000-97468-5 010 $a1-003-44368-0 010 $a1-57922-509-8 010 $a1-4416-5190-X 035 $a(CKB)2560000000013168 035 $a(EBL)911872 035 $a(OCoLC)635960955 035 $a(SSID)ssj0000414919 035 $a(PQKBManifestationID)12103327 035 $a(PQKBTitleCode)TC0000414919 035 $a(PQKBWorkID)10395038 035 $a(PQKB)10270259 035 $a(Au-PeEL)EBL911872 035 $a(CaPaEBR)ebr10545778 035 $a(MiAaPQ)EBC911872 035 $a(EXLCZ)992560000000013168 100 $a20091006d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aCooperative learning in higher education$b[electronic resource] $eacross the disciplines, across the academy /$fedited by Barbara J. Millis ; foreword by James Rhem 205 $a1st ed. 210 $aSterling, Va. $cStylus$d2010 215 $a1 online resource (254 p.) 225 1 $aNew pedagogies and practices for teaching in higher education series 300 $a"Published in association with the National Teaching and Learning Forum." 311 $a1-57922-328-1 320 $aIncludes bibliographical references and index. 327 $aCover; Contents; Foreword; Editor's Preface; 1 Why Faculty Should Adopt Cooperative Learning Approaches; 2 Cooperative Learning in Accounting; 3 Cooperative Learning in General Chemistry Through Process-Oriented Guided Inquiry Learning; 4 Cooperative Learning Structures Help College Students Reduce Math Anxiety and Succeed in Developmental Courses; 5 Cooperative Learning in Educational Psychology: Modeling Success for Future Teachers 327 $a6 Preparing the Next Generation of Engineering Educators and Researchers: Cooperative Learning in the Purdue University School of Engineering Education PhD Program7 The Interactive Lecture in a Research Methods and Statistics Class; 8 Want Brighter, Harder Working Students? Change Pedagogies!: Some Examples, Mainly from Biology; 9 Sequencing Cooperative Learning Activities in Literature Classes; 10 Implementing Cooperative Learning in Introductory Economics Courses; 11 Cooperative Learning in Geological Sciences; 12 Concluding Thoughts on This Volume; Bibliography; Contributors; Index; A; B 327 $aCD; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W 330 $aResearch has identified cooperative learning as one of the ten High Impact Practices that improve student learning. If you've been interested in cooperative learning, but wondered how it would work in your discipline, this book provides the necessary theory, and a wide range of concrete examples. Experienced users of cooperative learning demonstrate how they use it in settings as varied as a developmental mathematics course at a community college, and graduate courses in history and the sciences, and how it works in small and large classes, as well as in hybrid and online environments. The aut 410 0$aNew pedagogies and practices for teaching in higher education series. 606 $aGroup work in education$zUnited States 606 $aEducation, Higher$zUnited States 615 0$aGroup work in education 615 0$aEducation, Higher 676 $a378.1/76 701 $aMillis$b Barbara J$01466300 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910791225803321 996 $aCooperative learning in higher education$93676710 997 $aUNINA LEADER 04384nam 22006015 450 001 9910513597103321 005 20251225174946.0 010 $a3-030-92600-1 024 7 $a10.1007/978-3-030-92600-7 035 $a(MiAaPQ)EBC6825377 035 $a(Au-PeEL)EBL6825377 035 $a(CKB)20120241900041 035 $a(PPN)259385565 035 $a(OCoLC)1288466420 035 $a(DE-He213)978-3-030-92600-7 035 $a(EXLCZ)9920120241900041 100 $a20211211d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Intelligence in Data Science $e4th IFIP TC 12 International Conference, ICCIDS 2021, Chennai, India, March 18?20, 2021, Revised Selected Papers /$fedited by Vallidevi Krishnamurthy, Suresh Jaganathan, Kanchana Rajaram, Saraswathi Shunmuganathan 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (229 pages) 225 1 $aIFIP Advances in Information and Communication Technology,$x1868-422X ;$v611 311 08$aPrint version: Krishnamurthy, Vallidevi Computational Intelligence in Data Science Cham : Springer International Publishing AG,c2022 9783030925994 320 $aIncludes bibliographical references and index. 327 $aMachine Learning (ML), Deep Learning (DL), Internet of Things (IoT) -- A Scalable Data Pipeline for Realtime Geofencing using Apache Pulsar -- Crop Recommendation by Analysing the Soil Nutrients using Machine Learning Techniques: A Study -- Predict Customer churn in Banking based on Data Mining Techniques -- Early Prediction of Diabetes Disease Based on Data Mining Techniques -- An application driven IoT based rooftop farming model for Urban Agriculture -- Enhanced Ant Colony Optimization Algorithm for Optimizing Load balancing in Cloud Computing Platform -- Captioning of Image Conceptually using BI-LSTM technique -- Analysis of Land Cover type using Landsat-8 data -- Rule Based Combined Tagger for Marathi Text -- Evaluating candidate Answers based on derivative lexical similarity and space padding for the Arabic language -- Ontology Model for Spatio-Temporal Contexts in Smart Home Environments -- Automatic Detection of Building in Medium Density Image Using Morphological Operation -- A Liver Segmentation Algorithm with Interactive Error Correction for Abdominal CT Images: A Preliminary Study -- Pixel based Adversarial Attacks on Convolutional Neural Networks Models -- Continual Learning for Classification Problems: A Survey -- Detection of Flooded Regions from Satellite Images using Modified UNET -- Blockchain -- Blockchain based end-to-end tracking system for COVID patients -- Decentralized Application using Ethereum Blockchain on Performance Analysis considering E-voting system -- Enhanced Privacy Protection in Blockchain using SGX and Sidechains -- A Comparative Analysis of Blockchain Platform: Issues and Recommendations- Certificate Verification System. 330 $aThis book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science. 410 0$aIFIP Advances in Information and Communication Technology,$x1868-422X ;$v611 606 $aData mining 606 $aComputer networks 606 $aMachine learning 606 $aData Mining and Knowledge Discovery 606 $aComputer Communication Networks 606 $aMachine Learning 615 0$aData mining. 615 0$aComputer networks. 615 0$aMachine learning. 615 14$aData Mining and Knowledge Discovery. 615 24$aComputer Communication Networks. 615 24$aMachine Learning. 676 $a006.3 702 $aJaganathan$b Suresh$f1972- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910513597103321 996 $aComputational Intelligence in Data Science$92565845 997 $aUNINA