Pair programming improves student retention, confidence, and program quality
immc历届题目初中组

immc历届题目初中组
以下是历届IMMC初中组的题目:
1. 人工智能在教育领域的应用研究
2. 数字化时代下教育资源均衡发展的策略研究
3. 探究在线学习平台的设计与实现
4. 基于大数据的个性化学习推荐系统研究
5. 智能语音技术在教育领域的应用与优化
6. 虚拟现实(VR)在教育领域的应用与实践
7. 智能机器人辅助教学的研究与实践
8. 教育数据挖掘与分析在教育决策中的应用
9. 跨学科教育课程的设计与实施
10. 创新教育模式的研究与实践,如项目式学习、问题解决学习等
11. 家庭教育对孩子成长的影响及其实施策略的研究
12. 社区教育资源的整合与利用的研究
13. 教育信息化背景下教师专业发展的路径与方法研究
14. 数字化评估系统在教育领域的应用与实践
15. 环保教育在学校教育中的实施策略的研究
以上题目仅供参考,具体题目可能会根据不同的年份和地区有所变化。
dtnl练习题(打印版)

dtnl练习题(打印版)# DTNL 练习题(打印版)## 一、选择题1. 下列哪个选项不是深度学习(Deep Learning, DL)的典型应用?- A. 图像识别- B. 自然语言处理- C. 线性回归- D. 神经网络2. 在深度学习中,以下哪个术语与反向传播算法(Backpropagation)无关?- A. 梯度下降- B. 损失函数- C. 卷积神经网络- D. 特征提取## 二、填空题1. 深度学习模型中的激活函数通常用于引入________,以帮助模型学习复杂的数据模式。
2. 卷积神经网络(CNN)中的卷积层主要用于提取图像的________特征。
3. 在训练深度学习模型时,________是用于评估模型在训练集上的性能的指标。
## 三、简答题1. 简要描述什么是深度学习,并说明它与传统机器学习方法的主要区别。
2. 解释什么是过拟合(Overfitting),并给出避免过拟合的几种策略。
## 四、计算题给定一个简单的神经网络,包含一个输入层,两个隐藏层和一个输出层。
假设输入层有4个神经元,第一个隐藏层有8个神经元,第二个隐藏层有6个神经元,输出层有3个神经元。
如果输入层的激活值为[0.2, 0.5, 0.8, 1.0],第一个隐藏层的权重矩阵为:\[W_1 =\begin{bmatrix}0.1 & 0.2 & 0.3 & 0.4 \\0.5 & 0.6 & 0.7 & 0.8 \\0.9 & 1.0 & 1.1 & 1.2 \\\end{bmatrix}\]第一个隐藏层的偏置向量为 \( b_1 = [0.1, 0.2, 0.3, 0.4] \),激活函数为 ReLU。
请计算第一个隐藏层的输出激活值。
## 五、编程题编写一个简单的 Python 函数,该函数接受一个列表作为输入,返回列表中所有元素的和。
```pythondef sum_elements(input_list):# 你的代码pass```## 六、案例分析题考虑一个实际问题,例如图像识别、语音识别或自然语言处理等,描述如何使用深度学习技术来解决这个问题,并简要说明所选择的模型架构和训练过程。
PairProgramming( 成对编程 )

15
什么样的人适合做Pair Programming
Extreme Programming对实施的程序员提出了更高的要求。这种要求不是技 术水平,也不是学历水平也不是工作经验。这种要求是对一个人的心智,道 德,修养的更高要求。 程序员的四怕: 1) 怕自己看上去傻 2) 怕被认为是没用的 3) 怕自己变的不重要(过时)
Pair Programming中,任何一段代码都至少被两双眼睛看过,两个脑袋思考 过。结合Collective code ownership和小的Task (Small Engineering Task), 代码被不断的Review。
Copyright 2002 Chinaxp. All rights reserved
节都一齐肩并肩地,平等地,互补地进行开发工作。
其它领域的“Pair Working”:
•
•
越野赛车
驾驶飞机
Copyright 2002 Chinaxp. All rights reserved
2
Pair Programming的角色(Role)
• Driver The one who types • Navigator The one who watches the back • 角色可以互换的
•
效率低
Copyright 2002 Chinaxp. All rights reserved
10
为什么要Pair Programming
不间断的Code Review
Pair Programming提供不间断的Design review,Unit Test Review,Code Review,Document Review,避免了效果差的Team Code Review,也比抽 查式的Peer Code Review有更好的质量。(CMM Level 3)
1 Introduction Project Description

Project Description1IntroductionPair programming[1]transforms what has traditionally been a solitary activity into a coop-erative effort.Although pair programming has been practiced informally for many years, its use has become more prevalent as part of the Extreme Programming(XP)[2]software process.Even though it is a key practice of XP,pair programming can be used with other software development processes[3,4].In pair programming,two software developers share a single computer monitor and key-board.One of the developers,called the driver,controls the computer keyboard and mouse. The driver is responsible for entering software design,source code,and test cases.The second developer,called the navigator,examines the driver’s work,offering advice,suggest-ing corrections,and assisting with design decisions.The developers switch roles at regular intervals.Although role switching is an informal process,a typical interval is20minutes[5].Initial studies suggest that two programmers working together in the pair programming style produce code with fewer errors,with only a slight increase in total programmer time[3]. In addition,programmers using pair programming report improved mentoring[6],increased confidence in their solutions[7,8],and increased job satisfaction[6,9].At the university level,pair programming and extreme programming have been used in computer science courses as a teaching tool[10,11,12,13].Melnik and Maurer[14]found that students agreed with the statements“I personally like pair programming”,and“I believe that pair programming improves software quality.”McDowell et al.[11]found that allowing students to pair in an introductory programming course resulted in a greater percentage ofstudents completing the course.These students also were more likely than non-pairing stu-dents to select computer science related majors within one year of completing the course[8]. Students who paired also produced higher quality solutions than those who did not[15]. Williams[16]found that students who paired were less reliant on teaching assistants to an-swer their questions because they were able to help each other.These students were more active participants in their learning than unpaired students.One drawback with pair programming is its requirement that the pair members must be collocated.Some students have had difficulty pairing due to this restriction.If we can remove the collocation requirement,the benefits of pair programming could accrue to a wider audience.A tool that supports virtual pair programming without requiring the participants to physically meet would remove this impediment to the adoption of pair programming.We have developed this tool,and propose to evaluate it as a proof-of-concept in an introductory computer science course.2Results from Prior NSF SupportIn the2000/2001academic year,a study on the effectiveness of pair programming as a ped-agogical tool was conducted at the University of California at Santa Cruz(UCSC)(NSF Award EIA-0089989,$236,799from10/1/2000through9/30/2003,“Retaining Women in Computer Science:Impact of Pair Programming”).Students in four sections of an intro-ductory computer science course(Introduction to Programming)participated in the study. Pair programming was used in three of the sections,while in the fourth section students programmed alone.In all cases,students took exams individually.20%of each student’s grade was from their scores on the programming assignments,while the remaining80%camefrom their examination scores.Thus,the majority of each student’s grade was earned from individual work.There were404students who paired,and148who programmed by themselves.Student programming assignments were scored for functionality and readability.When students turned in a programming assignment,they also submitted a log indicating the amount of time they spent working on it.Students also answered three questions about their level of confidence in their solution,how much they enjoyed working on the programming assignment, and how satisfied they were with the process.Significant results from this study include:•90.8%of students who paired completed the course,compared with80.4%of non-pairers.A student completed the course if he or she took thefinal exam.•72.3%of students who paired passed the course,compared with62.8%of non-pairers.A student passed if he or she earned a grade of C or better in the course.•Students who paired received higher scores on their programming assignments.•Students in both groups performed similarly on thefinal exam,indicating that paired students did not get a‘free ride’on the programming portion of the course,but as-similated the material at least as well as students who worked alone.This is especially noteworthy considering that a greater percentage of paired students took thefinal.•Using a100point scale,students who paired reported greater confidence in their pro-gramming assignment solutions(mean89.4)than non-paired students(mean71.2).This was true for men(mean90.3vs.74.6)and women(mean86.8vs.63.0).The confidence gap between men and women was much smaller for paired students(3.5)then for non-paired students(11.6),suggesting that pairing boosts women’s confidence more than men’s.•Students who paired enjoyed working on their programming assignments more.•Students who paired had greater satisfaction with the programming process.•Students who paired were more likely to attempt the next computer science course (Introduction to Data Structures)and were equally likely to pass it as non-pairers.This is true even though none of the students paired in the second course.This indicates that pairing encouraged the students to try the next course,and did not have negative effects on their future performance,even though they had to work alone.•Students who paired were more likely to have declared a computer science major within one academic year after passing the course.It seems that pairing enhances the quality of student programs,and encourages students to pursue computer science degrees.Although pairing provides benefits to both male and female students,it appears to boost women students’confidence more than men’s.2.1PublicationsC.McDowell,L.Werner,H.Bullock,and J.Fernald,The Impact of Pair Programming on Student Performance and Pursuit of Computer Science Related Majors,Proceedings of the 25th International Conference on Software Engineering,2003,pp.602-607.C.McDowell,B.Hanks,and L.Werner,Experimenting with Pair Programming in the Classroom,Proceedings of8th Annual Conference on Innovation and Technology in Com-puter Science Education,2003.L.Williams,C.McDowell,N.Nagappan,H.Bullock,J.Fernald,and L.Werner,Building Pair Programming Knowledge through a Family of Experiments,Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering,2003.C.McDowell,B.Hanks,and L.Werner,What Constitutes a“Better”Student Program?, Poster presentation,SIGCSE Technical Symposium on Computer Science Education,2003.C.McDowell,H.Bullock,J.Fernald,and L.Werner,A Study of Pair-Programming in an Introductory Programming Course,Proceedings of the33rd ACM Technical Symposium on Computer Science Education,2002,pp.38-42.J.Bevan,L.Werner,and C.McDowell,Guidelines for the Use of Pair Programming in a Freshman Programming Class,Proceedings of the15th Conference on Software Engineering Education and Training,2002,pp.100-108.3Goals and ObjectivesThe results from our previous study are highly encouraging,and we believe that pair pro-gramming should be used more widely in the academic environment.However,there is a significant impediment to its adoption:the requirement that both partners must collocate.Some students have had difficulty physically meeting with their partner due to scheduling conflicts and personal constraints.Students have other classes and outside work that makes it difficult to schedule meetings[13].Some students may feel unsafe being on campus after dark.Other students have families that they must take care of,requiring their presence at home.These factors make pair programming difficult,undesirable,or impossible for some students.Thus,the benefits of pair programming,including greater success in introduc-tory programming courses,increased confidence,and greater retention in computer-relatedmajors,are potentially reduced or unavailable to these students.We believe that difficulties scheduling collocated meetings discourages some students, potentially resulting in their dropping the course.Other possible outcomes include students working alone rather than pairing on their assignments,and student dissatisfaction with their partners.We would like to reduce the amount of these incidents.We have developed a tool to support virtual pair programming,in which the partners do not have to physically meet.We propose to evaluate the tool in an introductory programming class.Since we expect that students willfind it easier to schedule meeting times with their partners,we hope to show that students who pair program while using this tool(1)spend less time working alone,(2)spend more time working on their programming assignments and as a result produce higher quality work,(3)are more satisfied with their working relationship with their partner,and(4)less frequently complain about their partners or request new partners than those who have to physically meet with their partner to pair.Although we do not expect our sample size to be large enough to demonstrate this,we also speculate that there will be greater student retention among students who virtually pair due to fewer scheduling problems.We also hope to show that students who use a distributed pair programming tool receive the same benefits as those who pair while collocated.Specifically,students who pair while distributed will perform as well as those who are collocated,will be equally confident in their programming solutions,and will have similar levels of enjoyment and satisfaction.Prior research in this area suggests that virtual pair programming can work[17,18]. However,these reports are more focused on distributed XP,and provide only anecdotalevidence that virtual pair programming is effective.No quantitative results are provided and no comparison is made between virtual and collocated pair programming.More recent work by Baheti et al.[19]suggests that distributed pairing can be as effec-tive as collocated pairing.Students who virtually paired using Microsoft’s NetMeeting[20] performed similarly to collocated pairs in terms of the grades they received on their project. Because student pairs worked on separate,self-selected projects direct comparison of their performance is difficult.If our proof-of-concept is successful,we hope to make the tool available to a wider audi-ence.We believe it would be applicable not only in introductory classes,but at all academic levels.Although we do not plan to try it here,we believe it would also be useful in distance learning environments.Finally,this tool may be useful in industry,where practices such as distributed teams and telecommuting conflict with collocated pair programming.4Detailed Project PlanWe plan to conduct an experiment using a modified version of the open-source Virtual Network Computing(VNC)[21]application.To virtually pair program,each student will use this modified verion of VNC,an Internet voice and text chat application such as AOL Instant Messenger(AIM)[22],and a computer headset.4.1Tool DescriptionBy observing student and professional pair programmers,we have noted that(1)pairs change roles regularly,but role changing is informal,(2)there is frequent gesturing at the screen,ac-companied by comments such as“What’s this?”or“Look here.”,(3)the partners’attentionis focused at the screen,not at each other,and(4)there is frequent conversation.These observations have led us to believe that a computer-supported collaborative work (CSCW)environment for virtual pair programming must support gesturing,conversation, and a shared workspace view.VNC,originally developed at AT&T Laboratories Cambridge (and now supported by RealVNC,Ltd.[23]),provides an excellent base for this environment.For our purposes,VNC’s main feature of interest is its ability to replicate a user’s com-puter desktop onto two client machines.The keyboard and mouse on either client can be used to control any application running on the desktop.VNC replicates application output to both clients,so that activity on either machine is reflected in the other’s display.In the standard version of VNC,multiple clients can connect to a VNC server.However, keyboard and mouse events from the separate clients are interlaced into a single stream that is sent to the host operating system.Although distributed pairs could use VNC this way,this behavior is not optimal.For example,if the navigator wishes to point to an area on the screen by using the mouse pointer,the driver has to refrain from using her mouse. Additionally,the navigator has to make certain that she doesn’t accidentally press any keys or use any mouse buttons while the driver is active.We believe it is essential for the remote navigator to have the ability to point at portions of the display.We have added a gesturing[24]feature to VNC,giving the driver and navigator separate cursors.This allows the navigator to identify or point out areas of the screen to the driver,without impacting the driver’s state.Floor control[25]must also be addressed by synchronous CSCW applications.Floor control allows one user of a shared application to take charge of it;only that user canprovide input to the application,while all other users are limited to viewing the application’s output.Most types offloor control are mediated by CSCW applications,but with social floor control the application’s users define their own techniques for turn-taking.Although socialfloor control can be chaotic,Greenberg[25]found that it can be effective in groups of two or three people.We believe that this is the best approach in a virtual pair programming tool.Because collocated pairs tend to casually change roles,we believe that an application-mediatedfloor control mechanism may actually hinder the pair programming process.Our observations of pair programming as screen-focused suggest that video is unnecessary in virtual pairing.Similar conclusions have been reported by others.Baheti et al.[19]gave web-cams to students,but the students did not use them.Maurer[17]also reports that video was not useful in distributed pairing.Collecting accurate data in pair programming experiments has been challenging[26],par-ticularly when the data is self-reported.We have enhanced VNC to automate the data collection process,providing more accurate records of the amount of time spent pairing, gesturing,driving,and navigating.4.2Pilot Study ResultsWe conducted a pilot study in the Winter2003term,using informal methods to gain insight into student use of the tool.Results of the pilot have been used to modify the tool as needed to support the formal experiment.For the pilot,two pairs of student volunteers in the introductory programming class were given a quick introduction to the tool and a four page handout describing how to use it. Using the tool allowed the students to work at home,instead of having to meet on-campusin one of the computing labs.The pairs had completed earlier programming assignments using collocated pairing,so the partners were already familiar with each other.These students provided valuable feedback on the tool.The majority of their suggestions for tool improvement were related to the user interface.Analysis of the logfiles created during the pilot also identified needed improvements with the tool’s data collection features.The students in the pilot also completed a questionnaire that solicited their opinions about the tool,the perceived benefits and drawbacks of virtual pair programming,and their confidence in their programming solutions.The students indicated that they felt that their confidence and the amount of time required to complete their programming assignments was unaffected by the tool.Perceived benefits of virtual pairing using the tool included working from home,not having to go to the lab,being able to work on their own computer with its familiar configuration,and having access to their refrigerator.Perceived drawbacks included lack of teaching assistant support (which is available in the labs)and lowfidelity audio using Instant Messenger.4.3Experimental PlansWe plan to evaluate virtual pair programming in two sections of an introductory program-ming class being offered in the Fall2003term.The total expected enrollment in these two sections is140students.In this course,students attend3.5hours of lecture and one hour of lab weekly.There are no special lab exercises;instead,students use this time to work on their programming homework and to have access to a teaching assistant.This course is required for computer science,computer engineering,and electrical engineering majors.The majority of students are majors,although some students from other disciplines enroll.We plan to conduct a randomized,single-factor with two treatments experiment[27].We will solicit student volunteers from the two sections of the course as participants.We will encourage participation by offering students a token payment of$10.All students in the class pair program on their assignments.Students are assigned a partner for the duration of the course.We will assign partners using the same method that we have used in past offerings of this course,including those in the NSF-funded study described above,with the proviso that pairs are composed of two experimental volunteers,or two non-volunteers.Each student provides a list of up to three classmates with whom they would like to pair.We will attempt to pair students based on their preferences.Students who do not indicate any preference will be arbitrarily paired,based on their ability to attend lab at the same time.Volunteer pairs will be randomly assigned to two equally-sized groups.One group will be randomly selected to use the tool.The second group will act as the control group,and the pairs in this group will program while collocated.Students in both groups will be expected to pair program on all of their programming assignments.Both groups will program while collocated for thefirst two programming assignments.We want the student pairs to have worked together prior to attempting distributed pairing.One reason for this is the pair jelling factor noted by Williams[7],which indicates that students have to learn to pair.Student pairs became more effective in comparison to individuals after they had completed theirfirst assignment.A second reason for having students work together before attempting distributed pairing is that we believe that they are more likely to have established a cooperative relationship.This is substantiated by Rocco’s[28]findingsthat individuals who had prior face-to-face interaction were more likely to cooperate in a distributed game than those who had never met.We understand that this is not representative of some situations,such as distance educa-tion,where students will not have the opportunity to physically meet before collaborating. However,since our students can meet,and do meet in class,we feel that preventing them from having an opportunity to establish a cooperative working relationship would be doing them a disservice.After completing their second programming assignment,students in the treatment group will be shown how to use the tool.They will also be given written instructions on the tool to use as a reference if needed.The students in this group will complete the remainder of their programming assignments using the tool.While this group will be able to pair while separated,we will not require them to do so.Because one of our primary motivations for providing this tool to students is to make it easier for them to schedule meetings,we do not want to prevent the students from scheduling collocated pairing if it is convenient for them. For example,some students mayfind it convenient to meet directly before or after class. Students in this group will be required to record the amount of time they spend pairing while collocated and while separated.To help monitor the proper use of pair programming,every student in the class(regardless of participation in the experiment)will be asked to keep a time log recording their effort on the programming assignments.They will record the total time they spent on the assignment, the percentage of the time they spent driving,and the amount of time they spent working alone.For the virtual pairing group,these times will be compared with the times recordedby the tool to gain insight into the accuracy of the student reported times.Participants in both groups will also be asked to respond to a questionnaire every time they turn in a programming assignment.The expected questions include:•How easy was it for you and your partner to arrange a time to work together?•How confident are you in your solution to this assignment?•How satisfied are you with the that way you and your partner worked together on this assignment?Students will respond to subjective questions using a7-point Likert scale.For example, the scale for satisfaction will range from1for very dissatisfied to7for very satisfied.To reduce potential bias,students’programming assignments will be graded by individ-uals who will not know which students are in which group.Each program will also be tested with a set of pre-defined test cases,and the percentage of passed test cases will be recorded. 5Experience and Capabilities of the Principal Investigators Charlie McDowell is professor of computer science at UCSC.He was Co-PI on NSF award EIA-0089989,“Retaining Women in Computer Science:Impact of Pair Programming”.The PI’s role in this study is to supervise the work of graduate student Brian Hanks in all aspects of the project.The experience gained from the just concluding study on the impact of pair programming should help ensure the success of this project.Also,where applicable the results from the previous study will be integrated into the proposed project.Brian Hanks is a Ph.D.Candidate at UCSC.He has20years of industrial experience in software engineering,including several years as director of a software process improvementorganization at a Fortune500company.He taught the introductory programming course in Winter2003,where students were required to pair program on their assignments.Mr.Hanks has been studying pair programming since2001.He will be responsible for conducting the study described here,under the supervision of Dr.McDowell.He has developed the tool described here,and conducted the pilot study of its effectiveness.His major contributions to this study include planning and implementing the experiment,data collection and analysis,and reporting the results.This work is the basis for Mr.Hanks’s Ph.D.dissertation.6Evaluation PlanWe will analyze the data collected during this experiment(questionnaire responses,home-work and exam grades,time sheets,logfiles,and black box test results)to confirm or refute our hypotheses.We hope tofind that students in the group using this tool •spend less time working alone,•spend more time working on their programming assignments and as a result produce higher quality work,•find it easier to schedule meetings with their partner,•are more satisfied with their working relationship with their partner,and•less frequently complain about their partners or request new partnersthan students in the collocated pairing group.We will also check that there are no negative consequences for students who have access to the tool,in terms of student confidence,enjoyment,and grades.We expect that studentsin both groups will be equally confident in their solutions and equally successful in the course, Thus,we predict that students who use the tool will enjoy advantages over those who do not,while still receiving the pedagogical benefits of pair programming.Assuming that our hypotheses are confirmed by this analysis,we plan to continue using the tool to support pair programming.7Dissemination of ResultsTo make our results known to the computer science education community,we plan to publish our results in conferences and journals that target this audience.These include:•The SIGCSE Technical Symposium on Computer Science Education.•The Conference on Software Engineering Education and Training.•The Conference on Innovation and Technology in Computer Science Education.•The education track of the International Conference on Software Engineering.•The journal Computer Science Education.To broaden dissemination of our results and provide exposure to industry as well as academia,we also plan to publish in conferences focused on agile methodologies,including the International Conference on eXtreme Programming and Agile Processes in Software En-gineering,and the XP/Agile Universe Conference.Additionally,we plan to submit results to conferences targeting empirical software engineering and computer-supported collaborative work.We also plan to make the tool available on the web,at an open source web site such as Source Forge,or in cooperation with RealVNC at their web site.References[1]Laurie Williams and Robert Kessler.Pair Programming Illuminated.Addison-Wesley,2002.[2]Kent Beck.Extreme Programming Explained:Embrace Change.Addison-Wesley,2000.[3]Laurie A.Williams.The Collaborative Software Process.PhD thesis,University of Utah,2000.[4]Randall W.Jensen.A pair programming experience.CrossTalk,The Journal of DefenseSoftware Engineering,March2003./crosstalk/2003/ 03/jensen.html.[5]Matevz Rostaher and Marjah Hericko.Tracking testfirst pair programming–an exper-iment.In Extreme Programming and Agile Methods-XP/Agile Universe2002,number 2418in LNCS,pages174–184.Springer,2002.[6]Alistair Cockburn and Laurie Williams.The costs and benefits of pair programming.InGiancarlo Succi and Michele Marchesi,editors,Extreme Programming Examined,pages 223–247.Addison-Wesley,2001.[7]Laurie A.Williams.Strengthening the case for pair programming.IEEE Software,17(4):19–25,July/August2000.[8]Charlie McDowell,Linda Werner,Heather Bullock,and Julian Fernald.The impactof pair programming on student performance and pursuit of computer science related majors.In Proceedings of the International Conference on Software Engineering(ICSE 2003),pages602–607,May3–10,2003.[9]John T.Nosek.The case for collaborative munications of the ACM,41(3):105–108,March1998.[10]Laurie Williams and Richard Upchurch.In support of student pair-programming.InProceedings of the32nd SIGCSE technical symposium on Computer Science Education, pages327–331,2001.[11]Charlie McDowell,Heather Bullock,Julian Fernald,and Linda Werner.A study ofpair-programming in an introductory programming course.In Proceedings of the33rd ACM Technical Symposium on Computer Science Education,pages38–42,February27 -March3,2002.[12]Matthias M.M¨u ller and Walter F.Tichy.Case study:Extreme programming in auniversity environment.In Proceedings of the23rd International Conference on Software Engineering,pages537–544,May2001.[13]David Umphress,T.Dean Hendrix,and James Cross.Software process in the classroom:The capstone project experience.IEEE Software,19(5):78–85,September/October 2002.[14]Grigori Melnik and Frank Maurer.Perceptions of agile practices:A student survey.InExtreme Programming and Agile Methods-XP/Agile Universe2002,number2418in LNCS,pages241–250.Springer,2002.[15]Charlie McDowell,Brian Hanks,and Linda Werner.Experimenting with pair program-ming in the classroom.In Proceedings of the8th Annual Conference on Innovation and Technology in Computer Science Education,June30–July2,2003.[16]Nachiappan Nagappan,Laurie Williams,Miram Ferzli,Eric Wiebe,Kai Yang,CarolMiller,and Suzanne Balik.Improving the CS1experience with pair programming.In Proceedings of the34th SIGCSE Technical Symposium on Computer Science Education, pages359–362,2003.[17]Frank Maurer.Supporting distributed extreme programming.In Extreme Programmingand Agile Methods-XP/Agile Universe2002,number2418in LNCS,pages13–22.Springer,2002.[18]Michael Kircher,Prashant Jain,Angelo Corsaro,and David Levine.Distributed eX-treme Programming.In Proceedings of XP2001,May2001./ conference/papers/Chapter16-Kircher+alii.pdf,current June14,2003.[19]Prashant Baheti,Edward Gehringer,and David Stotts.Exploring the efficacy of dis-tributed pair programming.In Extreme Programming and Agile Methods-XP/Agile Universe2002,number2418in LNCS,pages208–220.Springer,2002.[20]Microsoft meeting home page./windows/netmeeting/,current June14,2003.[21]Tristan Richardson,Quentin Stafford-Fraser,Kenneth R.Wood,and Andy Hopper.Virtual network computing.IEEE Internet Computing,2(1):33–38,January-February 1998.[22]America Online,Inc.AOL Instant Messenger home page.,currentJune14,2003.[23]RealVNC,Ltd.RealVNC home page.,current June8,2003.[24]Stephen Hayne,Mark Pendergast,and Saul Greenberg.Gesturing through cursors:Implementing multiple pointers in group support systems.In Proceedings of the26th Hawaii International Conference on System Science,volume4,pages4–12,1993. [25]Saul Greenberg.Sharing views and interactions with single-user applications.ACMSIGOIS Bulletin,11(2-3):227–237,April1990.。
MOOC《Python语言程度设计》第3周测试题

MOOC《Python语⾔程度设计》第3周测试题单项选择题点击选项选择正确答案,每题有且仅有⼀个正确答案1.pow(x, 0.5)能够计算x的平⽅根,计算负数的平⽅根将产⽣:A.⽆输出B.程序崩溃C.ValueError错误复数正确答案 D>>> pow(-1, 0.5)(6.123233995736766e-17+1j)2.以下关于字符串.strip()⽅法功能说明正确的是:A.去掉字符串两侧指定字符B.连接两个字符串序列C.按照指定字符分割字符串为数组D.替换字符串中特定字符正确答案 A"去掉字符串两侧指定字符"对应功能是.strip()"按照指定字符分割字符串为数组"对应功能是.split()"替换字符串中特定字符"对应功能是.replace()"连接两个字符串序列"对应功能是+操作符3.字符串是⼀个连续的字符序列,哪个选项可以实现打印字符信息的换⾏?A.使⽤转义符\\B.使⽤空格C.使⽤“\换⾏”D.使⽤\n正确答案 D换⾏符\n,与C语⾔中⼀致。
4.val=pow(2,1000),请⽤⼀⾏代码返回val结果的长度值。
A.len(str(val))B.len(pow(2,1000))C.len(val)D.以后均不正确正确答案 Alen(str(val))⾸先通过str(val)将数字类型val变成字符串,再通过len()获得字符串长度,即val的数字个数。
5.下⾯关于time库引⽤不正确的是?A.from time import strftimeB.from * import timeC.import timeD.from time import *正确答案 Bfrom * import time 应该是: from time import *6.哪个选项不是Python语⾔的整数类型?A.88B.0x9aC.0B1010D.0E99正确答案 D⼗进制:⼀般表⽰⼆进制:0b 或 0B 开头⼋进制:0o 或 0O 开头⼗六进制:0x 或 0X 开头没有0E开头7.关于整数类型的4种进制表⽰,哪个选项的描述是正确的?A.⼆进制、四进制、⼋进制、⼗六进制B.⼆进制、四进制、⼗进制、⼗六进制C.⼆进制、⼋进制、⼗进制、⼗六进制D.⼆进制、四进制、⼋进制、⼗进制正确答案 CPython不⽀持四进制整数8.哪个选项是Python语⾔%运算符的含义?A.x的y次幂B.x与y之商的余数C.x与y之商D.x与y的整数商正确答案 B%是取余数,与C语⾔相同。
pair work练习题

pair work练习题一、IntroductionPair work is an effective teaching method that involves students working together in pairs to complete a given task or activity. This approach promotes collaborative learning and enhances communication skills while providing an opportunity for students to learn from each other. In this article, we will explore the benefits of pair work and provide a variety of pair work exercises for different subjects and grade levels.二、Benefits of Pair Work1. Enhanced Communication Skills: Pair work facilitates verbal interaction between students, allowing them to practice and improve their speaking and listening skills. By actively engaging in conversations with their partners, students gain confidence in expressing their thoughts and ideas.2. Increased Engagement: Working in pairs encourages active participation from all students. It creates a supportive environment where students can contribute and share their perspectives, leading to a deeper understanding of the subject matter.3. Improved Problem-Solving Skills: Pair work exercises often involve problem-solving tasks that require students to think critically and find solutions together. Through collaboration, students develop their analytical and decision-making abilities, fostering a sense of teamwork.4. Diverse Perspectives: Pair work encourages students to work with different classmates, providing a platform for exchanging diverse viewpoints. This exposure to varying perspectives cultivates tolerance, empathy, and a broader understanding of different cultures and backgrounds.5. Individual Accountability: Each student in a pair is responsible for their own learning and contributions to the task. This individual accountability promotes independent thinking and self-reflection, enhancing the learning experience.三、Pair Work Exercises1. Pair Work Exercise for Language LearningObjective: To improve vocabulary and speaking skillsInstructions:a) Provide each pair with a set of vocabulary flashcards or a list of words related to a specific topic.b) Students take turns explaining the meaning or usage of the words to their partner while the partner listens and asks questions if needed.c) After completing the vocabulary discussion, the roles switch, allowing the other student to explain a new set of words.2. Pair Work Exercise for ScienceObjective: To reinforce understanding of scientific concepts through discussionInstructions:a) Assign pairs of students to research and prepare a short presentation on a specific scientific topic.b) Each pair presents their findings to the class, allowing other students to ask questions and engage in a discussion.c) The pairs should aim to explain complex concepts in a simplified manner, enhancing their own understanding while promoting active learning among classmates.3. Pair Work Exercise for MathematicsObjective: To solve mathematical problems collaborativelyInstructions:a) Provide each pair with a set of mathematical problems related to the current lesson.b) Students work together to solve the problems, discussing different strategies and approaches.c) After solving the problems, pairs share their solutions with the class and explain their reasoning behind each step.4. Pair Work Exercise for HistoryObjective: To analyze historical events and develop critical thinking skillsInstructions:a) Assign pairs with different historical events or periods to research.b) Each pair prepares a debate-style presentation arguing for or against a specific viewpoint related to their assigned topic.c) Pairs present their arguments to the class, engaging in a discussion and considering opposing perspectives.四、ConclusionPair work exercises provide numerous benefits in various subjects, fostering effective communication, critical thinking, and collaboration among students. By incorporating pair work into the classroom, educators can enhance student engagement and provide opportunities for active learning. These activities promote a positive learning environment and equip students with essential skills for their academic and personal growth.。
orange练习题

orange练习题一、基础概念理解1. 请简述数据挖掘的基本任务。
2. 解释什么是数据仓库及其在数据挖掘中的作用。
3. 描述决策树算法的基本原理。
4. 请说明Kmeans聚类算法的步骤。
5. 解释关联规则挖掘中的支持度、置信度和提升度。
6. 请阐述贝叶斯分类器的原理。
7. 说明遗传算法在数据挖掘中的应用。
8. 描述文本挖掘的主要技术和应用领域。
9. 请简述时间序列分析的基本方法。
10. 解释什么是集成学习及其优势。
二、Python编程基础1. 编写Python代码,实现一个简单的线性回归模型。
2. 使用Python编写代码,实现Kmeans聚类算法。
3. 编写代码,使用决策树算法对鸢尾花数据集进行分类。
4. 使用Python实现Apriori算法进行关联规则挖掘。
5. 编写代码,使用朴素贝叶斯分类器对文本数据进行分类。
6. 使用Python实现一个简单的神经网络模型。
7. 编写代码,使用随机森林算法对数据集进行分类。
8. 使用Python实现Adaboost算法。
9. 编写代码,使用KNN算法对数据集进行分类。
10. 实现一个基于Python的决策树可视化工具。
三、数据预处理1. 编写代码,实现数据标准化处理。
2. 编写代码,实现数据归一化处理。
3. 请描述数据缺失值处理的常见方法。
4. 编写代码,实现数据缺失值的填充。
5. 请简述数据倾斜的解决方法。
6. 编写代码,实现数据去重。
7. 请描述如何处理数据中的异常值。
8. 编写代码,实现数据集的划分(训练集和测试集)。
9. 请简述特征选择的方法。
10. 编写代码,实现特征选择。
四、模型评估与优化1. 请解释交叉验证的原理。
2. 编写代码,实现交叉验证。
3. 请描述混淆矩阵的概念。
4. 编写代码,计算混淆矩阵。
5. 请解释准确率、精确率、召回率和F1值的概念。
6. 编写代码,计算准确率、精确率、召回率和F1值。
7. 请描述过拟合和欠拟合的概念。
8. 编写代码,实现模型的过拟合和欠拟合检测。
NOI题库2.2括号匹配分析与题解(C )

if(S[i] == '(') //找到"(" {
left[j++] = i; //记录下标 S[i] = '$'; //假设该括号未匹配 }
9
else if(S[i] == ')') //找到")" {
if(left[j] >= 0) //有匹配的左括号,下标不为-1 {
$$ $
??
8
这样就写出了代码:
string s; while(getline(cin, S)) //读入整行 {
cout << S << endl; //输出原串 int left[102],j=0; //left[]记录所有"("在S中的下标,j只是指针 memset(left, -1, sizeof(left)); //初始化-1
1
问题描述
在某个字符串(长度不超过100)中有左 括号、右括号和大小写字母;规定(与常见 的算数式子一样)任何一个左括号都从内到 外与在它右边且距离最近的右括号匹配。写 一个程序,找到无法匹配的左括号和右括号 ,输出原来字符串,并在下一行标出不能匹 配的括号。不能匹配的左括号用“$”标注,不能 匹配的右括号用“?”标注。
2
输入
输入包括多组数据,每组数据一行,包 含一个字符串,只包含左右括号和大小写字 母,字符串长度不超过100
输出
对每组输出数据,输出两行,第一行包 含原始输入字符,第二行由"$","?"和空格组 成,"$"和"?"表示与之对应的左括号和右括号 不能匹配。
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Pair Programming Improves Student Retention, Confidence, and ProgramQualityCharlie McDowell and Linda WernerComputer Science DepartmentUniversity of California, Santa Cruz{charlie,linda}@,Heather E. Bullock and Julian FernaldPsychology DepartmentUniversity of California, Santa Cruz{hbullock,jfernald}@In recent years, the growth of extreme programming (XP) has brought considerable attention to collaborative programming. Developed over a fifteen year period by Kent Beck and his colleagues, Ron Jeffries and Ward Cunningham[1], XP is a computer software development approach that credits much of its success to the use of pair programming by all programmers, regardless of experience[2]. The pair programming dimension of XP requires that teams of two programmers work simultaneously on the same design, algorithm, code, or test. Sitting shoulder to shoulder at one computer, one member of the pair is the “designated driver,” actively creating code and controlling the keyboard and mouse. The “non-driver” constantly reviews the keyed data in order to identify tactical and strategic deficiencies, including erroneous syntax and logic, misspelling, and implementations that don't map to the design. After a designated period of time, the partners reverse roles. Code produced by only one partner is discarded, or reviewed collaboratively before it is integrated.Women and minorities continue to be underrepresented in computer science, and the number of women pursuing college majors in this area is declining. In 1984, 37% of computer science bachelor's degrees were awarded to women and in 1998 that percentage was down to 26% [3]. A number of variables have been proposed to account for this gender difference including: traditional socialization practices that reinforce math and science as male domains; lower confidence ratings and greater math anxiety among women; and women's tendency to take fewer advanced mathematics courses. The belief that computer science is a competitive, alienating field may further discourage women from pursuing careers in this area [4].Pair programming, when used as a form of collaborative learning, has been shown to increase the number of women (and men) persisting in their previously stated intent to pursue degrees in computer science. In addition, paired teams have been found to significantly outperform individual programmers in terms of functionality and readability, to report greater satisfaction with the problem-solving process, to have greater confidence in their solutions, and to be more likely to complete a programming assignment [5]. Nevertheless, many instructors continue to require students to complete programming assignments independently. Presumably, continued reliance on solo programming in academic settings is rooted in instructor concern that at least one of the partners in a pair will not learn as much as they would if they completed the assignment alone. In the worst case, one member of the pair might do essentially all of the work. Although this would not be “pair programming,” it is often difficult, if not impossible, to monitor how students actually spend their programming time and how closely they are following the pairing protocol.A Study of Pair Programming in Introductory Computer ScienceWe investigated the effects of pair programming on student performance and subsequent pursuit of computer science related degrees among both female and male college students taking an introductory programming course designed for computer science related majors (computer science, computer engineering, and information systems management). We collected data on 554 students who attempted the course at the University of California-Santa Cruz [6]. Data was collected from a total of 4 sections of the course: Fall 2000, Winter 2001 (2 sections), and Spring 2001. One of the principle investigators of this study, Charlie McDowell, taught the Fall and Spring sections of the course. The Winter 2001 sections were taught by UCSC faculty members not associated with this project.Students in the spring section were required to complete programming assignments independently. Students enrolled in the other sections were required to complete all assignments using pair programming. On the first day of class students in the pairing sections were given a brief 15 to 20 minute description of pair programming and instructed to read Williams and Kessler’s paper “All I Really Need to Know About Pair Programming I Learned in Kindergarten [7].” As an incentive to read the paper they were told that the first quiz might include a question about it.Students in the pairing sections submitted a list of three names of potential partners, and partners were assigned based on these preferences. In nearly all instances, students were assigned a partner from their list. Those that stated no preference were randomly assigned a partner. Whenever possible students remained with the same partner throughout the quarter, however, due to schedule changes and drops, a small number of partner reassignments were necessary. As a result of hardships such as heavy work schedules or living far from campus, seventeen students across the three pairing sections were permitted to program alone for various reasons. Data from these students was combined with the data from the students in the non-pairing section.Although each student was assigned to one 90-minute lab time per week, most programming assignments were completed outside of scheduled lab time. The labs functioned primarily as teaching assistant office hours. There were no specific in-lab assignments and attendance was not mandatory. Programming assignments were scored for functionality and readability. Along with each assignment students submitted a log indicating the amount of time they spent on the assignment (pairing students were asked to differentiate between time spent driving, reviewing, and alone), their level of confidence in their solution, how much they enjoyed working on the assignment, and how satisfied they were with the process.Regardless of whether they completed assignments in pairs, all students took exams independently. The final exam assessed students’ knowledge of programming concepts and their ability to write new code. We collected information about students SAT scores, the courses they took over the following year, and their major declarations a year after taking the class.An important assumption of this study was that all four of the sections of the course were similar in terms of students’ academic preparation to succeed. We found no difference in the SAT math scores among the four sections. We did find that the average SAT verbal score for one of the three pairing sections was lower than the score for the other two pairing sections. However, the difference was not significant when compared to the non-pairing section nor was there a significant difference between the pairing sections as a group and the non-pairing section. Because the difference was only between pairing sections it seemed acceptable.Persistence in computer scienceOne of the key hypotheses that was being tested by our study was the following:Women who program in pairs will have higher retention rates than women who program independently. Specifically we wanted to know if using pairing as a learning tool for beginning programmers would influence course completion rates and subsequent computer programming course taking behavior, both in terms of attempts and pass rates, and students’ decisions to major in computer science related fields.A comparison of students who used pair programming with those who didn’t indicated that pairers were significantly more likely to remain in the course through the final exam (90.8%) than were non-pairers. Among just those who took the final exam, the difference in pass rates between pairing (79.6%) and non-pairing students (78.2%) was not statistically significant. Williams and Kessler have proposed “pair pressure” as a possible explanation for higher completion rates among paired versus unpaired students [8]. According to Williams and Kessler, students who work in pairs may be more likely to complete programming courses because of the shared responsibility that results from collaborative partnerships. As a consequence, paired students may remain in the class for the sake of their partner. Although this is a plausible explanation, it is not supported by these data. The fact that in our study there was no difference in pass rates between pairers who completed the course and non-pairers who completed the course suggests that it was not simply the case that pairers were more likely to “stick it out,” but rather that a larger proportion of paired students were able to master enough of the course material to pass.For those students that passed the introductory programming course we followed them for one full academic year beyond the intro course. Consequently this analysis was limited to the 321 students who were still enrolled at UCSC three quarters after taking and passing the intro course.Among the students who were intending to pursue a computer science related major at the start of the introductory programming class, successfully passed the class with a “C” or better, and were still enrolled at UCSC a full year later(N=238; 187 men and 51 women), a significantly higher percentage of the students who had paired had gone on to attempt the subsequent programming course (Introduction to Data Structures) within a year (84.9%), than had the non-pairing students (66.7%). Separate analyses by gender of the effect of pairing on whether the subsequent course was attempted within a year revealed about an 18% difference between pairers and non-pairers for both women and men (73.8% of paired women vs. 55.6% of non-paired women, and 88.0% of paired men vs. 69.4% of unpaired men). The pairing effect was statistically significant for men but not for women. The increase in the percentage of students associated with pairing appears to be quite similar for men and women. The fact that this difference was statistically significant for men but not women is most likely attributable to the relatively small number of women (51 compared to 186 men) in this study.Among students that attempted the Data Structures course, the students from the pairing sections were more likely to pass the Data Structures course on the first attempt (65.5% vs. 40.0%). That is, students who paired in the introductory programming course were more likely to attempt the subsequent programming class and more likely to pass it than those who learned to program independently. This is particularly significant because students in the Data Structures course were required to complete all programming assignment individually. This indicates that there is not a problem with a significant number of weak students passing the intro course with the help of their partner, only to fail in the next course where they must program alone. The difference in pass rates between pair and non-pair students was similar for men (64.6% vs.37.5%) and women (68.3% vs. 44.4%), although for the women the difference was not statistically significant.Among the students initially intending a computer science major, and who passed the introductory course and remained at UCSC for at least a year, the pairing students were also more likely to have declared a computer science related major 1 year after completing the introductory programming class. This was the case for both women and men. Women who paired were more likely than women who worked independently to be in a computer science related major (59.5% vs. 22.2%). Similarly pairing men were also more likely to have declared a computer science related major 1 year later than men who worked alone (74% vs. 47.2%).Interestingly, the same pattern of results was observed among all students who successfully completed the introductory programming course and were still enrolled at UCSC a year later, regardless of whether they had initially been planning to major in one of the computer science related majors. Pairers were significantly more likely to have declared a computer science related major than non-pairers (56.9% vs. 33.8%), and that was the case for both men (59.5% vs. 41.1%), and women (46.3% vs. 11.1%).Table 1: Comparison of completion rates, pass rates, and persistence in the major. Numbers in bold indicatestatistically significant differences.Female Male AllPair Solo Pair Solo Pair Solo% that persisted in the course and took the final 88.1 79.5 91.781.5 90.880.4% of students taking the final that passed the class with C or better 74.2 74.2 81.379.5 79.678.2% of passers that took the 2nd programming course within 1 year 61.1 50.0 81.266.1 76.762.2% of passers that took the 2nd course within 1 year – restricted to those indicating a planned CS related major at start of intro course 73.855.6 88.69.4 84.966.7% of those taking the 2nd course that passed it on the first attempt 68.3 44.4 64.637.5 65.540.0% of passers still at UCSC 1 year later that declared a CS major 46.3 11.1 59.541.1 56.933.8% of passers still at UCSC 1 year later that declared a CS major – restricted to those indicating a planned CS related major at start of intro course 59.522.2 74.47.2 70.842.2Course PerformanceIn addition to completion and pass rates, we looked at specific parts of the course performance. We measured two related, but distinct indicators of course mastery. The first, the quality of the programs that students produce was operationalized as student’s normalized average score on the graded programming assignments. The second is the extent to which students are able to apply the concepts covered during the course. We used final exam scores, which all studentstook independently regardless of whether they paired or not, as the measure of the extent to which they had learned the material. For the following analyses we included only the 486 students who completed the course, defined as taking the final exam.Among students who completed the class, those who paired produced significantly better programs (86.6%) than those who worked alone (68.1%). There was no significant gender difference in average programming scores (men’s and women’s scores were 81.9% and 82.5% respectively), nor was there an interaction between gender and pairing. In other words, pairing was associated with significantly higher scores for both women and men.It may be that the reluctance of some computer science faculty to use pair programming in their classes is due to a concern that at least some students will “earn” grades that predominantly reflect their partner’s work. It is possible, for example, that the pairing students in our study earned higher average programming scores simply because weaker students received scores that were primarily due to the work of the stronger student in the pair, thus artificially inflating the average programming scores of the pairers.Elsewhere we have argued that the very process of working collaboratively enhances the quality of programs that pairs produce [9]. In that paper we compared the two sections of the introductory programming course that were taught by the same instructor, and for which assignments were intentionally designed to be equivalent. We found that the average score on programming assignments of all of the students in the pairing section was significantly higher than the average score of the top 50% (based on final exam scores) of the non-pairing section.Because the students in different sections of this study did not complete the exact same programming assignments, we did a follow-up study [10] in which a section of pairing students was given the exact same programming assignments as the non-pairing students from our original study. In that study we again found that the programs produced by the pairing students were significantly better than those produced by the non-pairing students, although the difference was not as great as in the original study. This suggests that some of the difference reported in our main study could be from variations in the difficulty of the assignment, but that the overall conclusion is unchanged.Because all of the students in this study took the final exam independently, we considered final exam scores to be a strong indication of the extent to which students had mastered the course material. There was no significant difference in the average final exam of the pairers (75.2%) and the non-pairers (74.4%). This finding strongly suggests that a student’s ability to independently apply concepts to novel problems is not compromised by learning to program in pairs. Indeed, considering that a significantly greater percentage of the students who paired took the final, it seems that learning to program in pairs results in mastery for a greater percentage of students.Confidence and EnjoymentOf course the most important goal for students in any class is mastery of the material. This is certainly the case for introductory programming courses, where future success is dependent on a strong foundational knowledge. However, subjective experiences in introductory programming courses may also contribute to decisions about whether to pursue computer science related degrees. For this reason it is important to understand how the experience of pairing influences students’ confidence and enjoyment of their work. Students responded to the following questions in their logs completed after each graded programming assignment.Confidence: On a scale from 0 (not at all confident) to 100 (very confident), how confident are you in your solution to this assignment?Enjoyment: How much did you enjoy working on this programming assignment? (1=not at all, 7=very much) Pairing students enjoyed working on programming assignments (M=5.15) more than non-pairing students (M=4.69), Likewise, among just the males pairing students reported greater enjoyment (M=5.23) than non-pairing students (M=4.75). Women pairing students also reported greater enjoyment (M=4.90) than non-pairing women (M=4.65), however this difference was not significant. There was also no significant difference in the reported enjoyment of all women versus all men.In addition to enjoying their coursework more, students who paired reported significantly higher confidence in their program solutions (89.4%) than students who worked independently (71.2%), Consistent with findings in other areas, men were significantly more confident (87.0%) than women (81.1%). There was also a significant interaction between pairing and gender with regard to reported confidence. Follow-up tests of the interaction indicated that pairing resulted in more confidence for both women (86.8% vs. 63.0%) and men (90.3% vs. 74.6%). However, the 24% increase in confidence that pairing afforded women was even greater than the 15% confidence boost experienced by men who had the benefit ofFigure 1pairing. The result was a significant decrease of a gender gap in confidence as shown in .100%AllWomen MenFigure 1: Confidence in program solutions - closing one gender gap.ConclusionThe results of this study provide some of the most compelling evidence to date of the effectiveness of pair programming as a pedagogical tool. It appears that pairing bolsters course completion and consequently course pass rates, and contributes to greater persistence in computer science related majors. Moreover, students who pair were more likely to pass the subsequent programming course which required them to work alone. This is a strong indicator that pairing did not result in a significant number of students passing the course without learning how to program due to a free-ride from their partner. The pairing students also produce higher quality programs, are more confident in their work, and enjoy it more. We hope these findings will encourage instructors to use pair programming not only in their introductory courses, but also in their upper level courses.The continued underrepresentation of women in computer science underscores the need for strategies that foster women’s interest and promote their success[4]. Pair programming appears to be one such approach. That the benefits associated with pair programming extend to both men and women speaks to its broad-based appeal. As we continue to investigate the effects of this technique on attracting and retaining female students, parallel research investigating these phenomena in the workplace is also needed.AcknowledgmentsThis work was funded by National Science Foundation grant EIA-0089989. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.References[1] Beck, K., Extreme Programming Explained: Embrace Change . 2000, Reading, Mass: Addison-Wesley.[2] Williams, L., et al., Strengthening the Case for Pair Programming. 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