Effectiveness of problem based learning in a materials science course in the engineering curriculum

基于问题的学习在工程课程材料科学课程中的有效性

基本信息

  • 批准号:
    0836914
  • 负责人:
  • 金额:
    $ 15万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-06-01 至 2011-11-30
  • 项目状态:
    已结题

项目摘要

Engineering - Other (59)Problem solving is the primary intellectual activity of engineers and enhancing problem-solving is essential for preparing engineering students for their future workplace. In addition, new pedagogies such as problem-based learning (PBL) have been shown to be highly effective in improving overall student learning. Through this project, PBL activities are being developed for a material science course and are being implemented in an undergraduate course for mechanical engineering students. Learning outcomes from the PBL-based course are being compared to those obtained in a traditional topics-based course. Engineering curricula typically include PBL-like activities in the capstone design course; however, in this project, PBL is being introduced at the sophomore level to motivate learning and improve students' ability to solve ill-structured problems. The results from this project are being rigorously evaluated by both qualitative and quantitative means. Project results are being disseminated through a website, journal articles, and workshops for engineering faculty who may be interested in implementing PBL techniques in their undergraduate courses.
工程 - 其他 (59) 解决问题是工程师的主要智力活动,增强解决问题的能力对于工程专业学生为未来的工作做好准备至关重要。此外,基于问题的学习(PBL)等新教学法已被证明在提高学生整体学习方面非常有效。通过该项目,正在为材料科学课程开发 PBL 活动,并在机械工程学生的本科课程中实施。基于 PBL 的课程的学习成果与传统的基于主题的课程获得的学习成果进行了比较。工程课程通常包括顶点设计课程中类似 PBL 的活动;然而,在这个项目中,PBL 被引入到二年级,以激励学习并提高学生解决结构不良问题的能力。该项目的结果正在通过定性和定量手段进行严格评估。项目结果正在通过网站、期刊文章和研讨会为可能有兴趣在本科课程中实施 PBL 技术的工程学院传播。

项目成果

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Sanjeev Khanna其他文献

Almost-Tight Bounds on Preserving Cuts in Classes of Submodular Hypergraphs
子模超图类中保留割断的几乎紧界
Theory of Computing
计算理论
  • DOI:
    10.4086/toc
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alexandr Andoni;Nikhil Bansal;P. Beame;Giuseppe Italiano;Sanjeev Khanna;Ryan O’Donnell;T. Pitassi;T. Rabin;Tim Roughgarden;Clifford Stein;Rocco Servedio;Amir Abboud;Nima Anari;Ibm Srinivasan Arunachalam;T. J. Watson;Research Center;Petra Berenbrink;Aaron Bernstein;Aditya Bhaskara;Sayan Bhattacharya;Eric Blais;H. Bodlaender;Adam Bouland;Anne Broadbent;Mark Bun;Timothy Chan;Arkadev Chattopadhyay;Xue Chen;Gil Cohen;Dana Dachman;Anindya De;Shahar Dobzhinski;Zhiyi Huang;Ken;Robin Kothari;Marvin Künnemann;Tu Kaiserslautern;Rasmus Kyng;E. Zurich;Sophie Laplante;D. Lokshtanov;S. Mahabadi;Nicole Megow;Ankur Moitra;Technion Shay Moran;Google Research;Christopher Musco;Prasad Raghavendra;Alex Russell;Laura Sanità;Alex Slivkins;David Steurer;Epfl Ola Svensson;Chaitanya Swamy;Madhur Tulsiani;Christos Tzamos;Andreas Wiese;Mary Wootters;Huacheng Yu;Aaron Potechin;Aaron Sidford;Aarushi Goel;Aayush Jain;Abhiram Natarajan;Abhishek Shetty;Adam Karczmarz;Adam O’Neill;Aditi Dudeja;Aditi Laddha;Aditya Krishnan;Adrian Vladu Afrouz;J. Ameli;Ainesh Bakshi;Akihito Soeda;Akshay Krishnamurthy;Albert Cheu;A. Grilo;Alex Wein;Alexander Belov;Alexander Block;Alexander Golovnev;Alexander Poremba;Alexander Shen;Alexander Skopalik;Alexandra Henzinger;Alexandros Hollender;Ali Parviz;Alkis Kalavasis;Allen Liu;Aloni Cohen;Amartya Shankha;Biswas Amey;Bhangale Amin;Coja;Yehudayoff Amir;Zandieh Amit;Daniely Amit;Kumar Amnon;Ta;Beimel Anand;Louis Anand Natarajan;Anders Claesson;André Chailloux;André Nusser;Andrea Coladangelo;Andrea Lincoln;Andreas Björklund;Andreas Maggiori;A. Krokhin;A. Romashchenko;Andrej Risteski;Anirban Chowdhury;Anirudh Krishna;A. Mukherjee;Ankit Garg;Anna Karlin;Anthony Leverrier;Antonio Blanca;A. Antoniadis;Anupam Gupta;Anupam Prakash;A. Singh;Aravindan Vijayaraghavan;Argyrios Deligkas;Ariel Kulik;Ariel Schvartzman;Ariel Shaulker;A. Cornelissen;Arka Rai;Choudhuri Arkady;Yerukhimovich Arnab;Bhattacharyya Arthur Mehta;Artur Czumaj;A. Backurs;A. Jambulapati;Ashley Montanaro;A. Sah;A. Mantri;Aviad Rubinstein;Avishay Tal;Badih Ghazi;Bartek Blaszczyszyn;Benjamin Moseley;Benny Pinkas;Bento Natura;Bernhard Haeupler;Bill Fefferman;B. Mance;Binghui Peng;Bingkai Lin;B. Sinaimeri;Bo Waggoner;Bodo Manthey;Bohdan Kivva;Brendan Lucier Bundit;Laekhanukit Burak;Sahinoglu Cameron;Seth Chaodong Zheng;Charles Carlson;Chen;Chenghao Guo;Chenglin Fan;Chenwei Wu;Chethan Kamath;Chi Jin;J. Thaler;Jyun;Kaave Hosseini;Kaito Fujii;Kamesh Munagala;Kangning Wang;Kanstantsin Pashkovich;Karl Bringmann Karol;Wegrzycki Karteek;Sreenivasaiah Karthik;Chandrasekaran Karthik;Sankararaman Karthik;C. S. K. Green;Larsen Kasturi;Varadarajan Keita;Xagawa Kent Quanrud;Kevin Schewior;Kevin Tian;Kilian Risse;Kirankumar Shiragur;K. Pruhs;K. Efremenko;Konstantin Makarychev;Konstantin Zabarnyi;Krišj¯anis Pr¯usis;Kuan Cheng;Kuikui Liu;Kunal Marwaha;Lars Rohwedder László;Kozma László;A. Végh;L'eo Colisson;Leo de Castro;Leonid Barenboim Letong;Li;Li;L. Roditty;Lieven De;Lathauwer Lijie;Chen Lior;Eldar Lior;Rotem Luca Zanetti;Luisa Sinisclachi;Luke Postle;Luowen Qian;Lydia Zakynthinou;Mahbod Majid;Makrand Sinha;Malin Rau Manas;Jyoti Kashyop;Manolis Zampetakis;Maoyuan Song;Marc Roth;Marc Vinyals;Marcin Bieńkowski;Marcin Pilipczuk;Marco Molinaro;Marcus Michelen;Mark de Berg;M. Jerrum;Mark Sellke;Mark Zhandry;Markus Bläser;Markus Lohrey;Marshall Ball;Marthe Bonamy;Martin Fürer;Martin Hoefer;M. Kokainis;Masahiro Hachimori;Matteo Castiglioni;Matthias Englert;Matti Karppa;Max Hahn;Max Hopkins;Maximilian Probst;Gutenberg Mayank Goswami;Mehtaab Sawhney;Meike Hatzel;Meng He;Mengxiao Zhang;Meni Sadigurski;M. Parter;M. Dinitz;Michael Elkin;Michael Kapralov;Michael Kearns;James R. Lee;Sudatta Bhattacharya;Michal Koucký;Hadley Black;Deeparnab Chakrabarty;C. Seshadhri;Mahsa Derakhshan;Naveen Durvasula;Nika Haghtalab;Peter Kiss;Thatchaphol Saranurak;Soheil Behnezhad;M. Roghani;Hung Le;Shay Solomon;Václav Rozhon;Anders Martinsson;Christoph Grunau;G. Z. —. Eth;Zurich;Switzerland;Morris Yau — Massachusetts;Noah Golowich;Dhruv Rohatgi — Massachusetts;Qinghua Liu;Praneeth Netrapalli;Csaba Szepesvári;Debarati Das;Jacob Gilbert;Mohammadtaghi Hajiaghayi;Tomasz Kociumaka;B. Saha;K. Bringmann;Nick Fischer — Weizmann;Ce Jin;Yinzhan Xu — Massachusetts;Virginia Vassilevska Williams;Yinzhan Xu;Josh Alman;Kevin Rao;Hamed Hatami;—. XiangMeng;McGill University;Edith Cohen;Xin Lyu;Tamás Jelani Nelson;Uri Stemmer — Google;Research;Daniel Alabi;Pravesh K. Kothari;Pranay Tankala;Prayaag Venkat;Fred Zhang;Samuel B. Hopkins;Gautam Kamath;Shyam Narayanan — Massachusetts;Marco Gaboardi;R. Impagliazzo;Rex Lei;Satchit Sivakumar;Jessica Sorrell;T. Korhonen;Marco Bressan;Matthias Lanzinger;Huck Bennett;Mahdi Cheraghchi;V. Guruswami;João Ribeiro;Jan Dreier;Nikolas Mählmann;Sebastian Siebertz — TU Wien;The Randomized k ;Conjecture Is;False;Sébastien Bubeck;Christian Coester;Yuval Rabani — Microsoft;Wei;Ethan Mook;Daniel Wichs;Joshua Brakensiek;Sai Sandeep — Stanford;University;Lorenzo Ciardo;Stanislav Živný;Amey Bhangale;Subhash Khot;Dor Minzer;David Ellis;Guy Kindler;Noam Lifshitz;Ronen Eldan;Dan Mikulincer;George Christodoulou;E. Koutsoupias;Annamária Kovács;José Correa;Andrés Cristi;Xi Chen;Matheus Venturyne;Xavier Ferreira;David C. Parkes;Yang Cai;Jinzhao Wu;Zhengyang Liu;Zeyu Ren;Zihe Wang;Ravishankar Krishnaswamy;Shi Li;Varun Suriyanarayana
  • 通讯作者:
    Varun Suriyanarayana
ScholarlyCommons ScholarlyCommons
学术共享 学术共享
On propagation of deletions and annotations through views
关于通过视图传播删除和注释
Maximum Bipartite Matching in ?2+?(1) Time via a Combinatorial Algorithm
通过组合算法在 ?2+?(1) 时间内实现最大二分匹配

Sanjeev Khanna的其他文献

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{{ truncateString('Sanjeev Khanna', 18)}}的其他基金

Collaborative Research: AF: Medium: Fast Combinatorial Algorithms for (Dynamic) Matchings and Shortest Paths
合作研究:AF:中:(动态)匹配和最短路径的快速组合算法
  • 批准号:
    2402284
  • 财政年份:
    2024
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
AF: Small: Sublinear Algorithms for Flows, Matchings, and Routing Problems
AF:小:流、匹配和路由问题的次线性算法
  • 批准号:
    2008305
  • 财政年份:
    2020
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
AF: Small: Sublinear Algorithms for Graph Optimization Problems
AF:小:图优化问题的次线性算法
  • 批准号:
    1617851
  • 财政年份:
    2016
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
AF: EAGER: Small Space Algorithms and Representations for Graph Optimization Problems
AF:EAGER:图优化问题的小空间算法和表示
  • 批准号:
    1552909
  • 财政年份:
    2015
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
AF: Small: Cut, Flow, and Matching Problems in Graphs
AF:小:图中的切割、流动和匹配问题
  • 批准号:
    1116961
  • 财政年份:
    2011
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
III: Medium: Collaborative Research: Optimization with Sparse Priors--Algorithms, Indices, and Economic Incentives
III:媒介:协作研究:稀疏先验优化——算法、指数和经济激励
  • 批准号:
    0904314
  • 财政年份:
    2009
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
Cuts, Flows, and Network Routing
剪切、流和网络路由
  • 批准号:
    0635084
  • 财政年份:
    2006
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Collaborative Research: CT-T: DoS Prevention in Shared Channels
合作研究:CT-T:共享通道中的 DoS 预防
  • 批准号:
    0524269
  • 财政年份:
    2005
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Acquisition of a Nanomechanical Testing Platform to Establish a User Center for Nanomecanical Characterization Materials
收购纳米力学测试平台,建立纳米力学表征材料用户中心
  • 批准号:
    0420859
  • 财政年份:
    2004
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Development and Manufacturing of Highly Damage Resistant Fiber Glass Reinforced Window Panels for Buildings in Hurricane Prone Areas
为飓风多发地区的建筑物开发和制造高抗损伤玻璃纤维增​​强窗板
  • 批准号:
    0196428
  • 财政年份:
    2001
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant

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