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In addition, as students tend to procrastinate, IDEOL is a useful tool to facilitate, monitor, and report student progress in extended programming exercises.. Through using IDEOL for t

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Learning and Practicing Object-Oriented

Programming Using a Collaborative Web-based IDE

Vu Nguyen, Hai H Dang, Kha N Do, Thu D Tran

Faculty of Information Technology University of Science, Vietnam National University – Ho Chi Minh city

{nvu, dhhai, dnkha, tdthu}@fit.hcmus.edu.vn

Abstract— Collaborative programming is an effective approach

to software development, improving software quality, programmer’s

satisfaction and shortening delivery time This study examines the

application of a collaborative Web-based IDE named IDEOL to

execute a four-week multi-submission programming assignment in

an introductory object-oriented programming class Forty eight

students forming 24 two-member groups in class used the IDE to

interact and write source code required by the project All

collaborative and programming activities performed by students

were recorded by IDEOL The results of the study shows that

students tend to postpone their programming work until the

submission dates This study also provides an approach to

designing and executing an extended programming exercises,

which receives high student satisfaction Our results imply that

IDEOL is a useful environment for students to collaborate, learn,

and practice programming to improve their learning satisfaction

In addition, as students tend to procrastinate, IDEOL is a useful

tool to facilitate, monitor, and report student progress in extended

programming exercises

Keywords—Collaborative IDE; Web-based IDE; programming

exercise; collaboration; interaction

Internet technologies play a key role in teaching and

learn-ing programmlearn-ing languages On the one hand, Internet

technologies enhance collaboration and interaction between all

participants involving in the education process They help

improve learning performance and satisfaction [2][3][7] In

collaborative environments, students share their perspectives,

listen to the views of others, and observe what others are

doing to generate knowledge and skills [12][8] On the other

hand, the increased trends in distributed programming teams

require instructors to prepare students necessary skills to

collaborate effectively with members in such environments

Collaborative programming has been shown to be an

effec-tive approach to accelerating problem-solving process,

improving code design and shortening code length, increasing

programmers’ satisfaction, which result in improving the

programmer productivity and quality of source code delivered

[4][5][6] Many Internet tools have been used to support

collaboration and interaction in programming groups, ranging

from general-purpose products such as Skype, Google Chat, and Facebook to specifically tailored systems for development collaboration such as RECIPE [5], Collabode [13], Saros [14], and ATCoPE [15]

We developed a collaborative web-based IDE called IDEOL to support teaching programming classes [1] Beside the essential features of a typical integrated development environment such as source code editing, compiling, building, and debugging, the system provides collaboration and interaction capabilities via Web This system allows students and instructors to communicate synchronously and asyn-chronously by employing social network capabilities such as commenting, liking, and sharing The system allows five most common modes of interaction, including student-student, student-instructor, student-content, instructor-instructor, and instructor-content [16] [17] One key feature of the system is the capability to record user activities, including date and time occurred, time spent on interaction, involving objects and participants, and other attributes of interaction On IDEOL, students are not constrained to posting questions or answers, but they can post any message or comment, which may be a question, an answer, a status, or simply a note on what they are doing or feeling

In this study, we use IDEOL for implementing a four-week programming project in an object-oriented programming course All 48 second-year students from two classes taking the OOP course were assigned into 24 two-member groups, and each group was required to use IDEOL to perform the same project All groups worked on the exercise followed the same scenario: overall description of the work was given in the first week; assignments were posted at the beginning of each week; and each group was required to submit its results

at the end of each week All collaborations were carried out on the IDEOL system, which records all transactions involved Our objective is to investigate the use of IDEOL to facili-tate learning and practicing OOP through the multi-submission programming project We will describe how to use IDEOL to design and execute the project and how IDEOL

978-1-4799-3922-0/14/$31.00 ©2014 IEEE

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helps facilitate collaboration, interaction, and participation of

students Through using IDEOL for the programming project,

we will investigate student’s working and collaborating

profiles on the system and student satisfaction with the system

and the project

Forty eight students forming 24 two-member groups in

class used IDEOL to interact and write source code required

by the project All collaborative and programming activities

performed by students were recorded by the IDE The results

of the study show that students tend to postpone their

gramming work until the submission dates, but their

ration activities were not delayed as much The results also

show high student satisfaction when using the system to

collaborate and complete the exercise In addition, this study

provides an approach to designing and executing an extended

programming exercise, which is useful to cope with student’s

procrastination problem

II IDEOL:ACOLLABORATIVE ENVIRONMENT FOR

A The IDEOL architecture

Fig 2 shows the high level architecture of IDEOL In a

traditional lab session, students and instructors can discuss

issues directly at a computer running IDEOL The system

provides core tools for a junior-level programming course,

including source-code editing, compilation, execution and

debugging In this face-to-face setting, learner-instructor and

learner interactions are facilitated through

learner-content-instructor interactions Contents can be delivered in an integrated manner, embedded inside IDE tools Thus, interactions between learner-content-instructor through various tools are united within a single environment

When out of class, students can interact with other students and instructors online The system supports all three types of interactions online through content sharing and tagging, real-time synchronous collaboration and discussion channels

B IDEOL key features

IDEOL provides a real-time interactive environment, with core functionalities of a traditional IDE combined with social media mechanism to foster interactions (see Fig 1 and Fig 2) The system also provides data collection mechanisms for analytics

A real-time interactive environment with awareness

Team members can simultaneously work on a single or multiple source files and have changes by other members updated instantly through the editor Working statuses of members are updated concurrently: one can easily be notified which files the other members are viewing or editing; whether they are testing or debugging the application; or whether they are trying to solve an issue through the discussion board

An integrated discussion channel with tagging (see Fig

1) The discussion board is organized into threads with each being an issue or a topic This feature allows users to tag files, specific lines of code, running and debugging results in a discussion

Fig 1 IDEOL Main Screen

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Build automation, an interactive execution tool for

console applications, and a debugger This feature uses the

GNU Compiler Collection tools that allow users to obtain and

examine outputs while compiling and debugging

Activity tracking The system collects activity data

through requests of services sent to servers Complex

components at the client side can also track and frequently

report non-serviced behaviors, for example, scrolling to view a

document These data allow instructors to monitor students’

working progress and trace changes, so that they can be aware

of each individual’s strengths and weaknesses and give

appropriate adjustments

III EXPERIMENT DESIGN

In this section, we describe our IDEOL experiment through

an extended exercise for an introductory OOP course

A Research Questions

In this study, we are interested using IDEOL to facilitate

collaboration and collect data for analysis through the

extended multi-submission programming exercise We

investigate how often students collaborate, how much their

satisfaction is when using IDEOL More specifically, our

research questions are:

RQ1: Given the exercise that requires them to submit work frequently, how often do students collaborate and do pro-gramming work via IDEOL?

RQ2: How much are students satisfied with the design of the project, the IDEOL system, and collaboration?

B The OOP Project

The OOP course at our school includes 15 weeks of lec-tures and 12 weeks of practicing labs, 2 hours each After introducing concepts of the OOP approach, the course guides students towards OO analysis and design, where students are required to practice OO modeling techniques

In this experiment, we prepared a 4-week lab project that started at the 5th week of practicing labs (at which time the students had been through half of the course) The project is divided into smaller tasks with each taking approximately a day to complete in a week The full requirements were not provided to the students at the start of the project Instead, we introduced them as newly added requirements every week, to simulate changes and to challenge students to change the design accordingly

This project can be seen as a scenario-based game-like group assignment Each week a group must complete the requirements of a task, and thus earns new knowledge At the

Source code repository

Build automation

Debugger

User program

Build log

Execution Output

Debug output

Discussion board

Instructor

Student

HTTP/REST

WebSocket

Edit source code Build program Run tests etc.

Watch edits Discuss Add new issue Debug etc.

Add new assignments Provide project template Monitor progress Post questions Discuss Answer questions etc.

Web browser

Web browser

Web browser

Fig 2 IDEOL Architecture

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end of the week, instructors would give comments and

explanations on students’ work Students can then move on to

the next task, with a sample solution to the previous task

provided by the instructors Since each task depends on

solutions to the previous tasks, each group must review their

current solution against the solution provided by the

instruc-tors At the end of these iterations there can be extremely

complicated solutions, or some simple yet delicate solutions to

a complex problem

This scenario-based project therefore requires a non-trivial

problem In this experiment, we chose the problem of

representing graphical objects and their persistence in the

SVG XML-based format1 The project was organized as

follows:

• Lab week 1: introduction of two basic graphical objects,

line and circle, and their properties according to the SVG

1.1 specification Each group was required to create a

preliminary version of the UML class diagram for the

objects

• Lab week 2: introduction of other basic SVG graphical

objects, including rectangle, ellipse, polygon and

poly-line Tasks included creating classes to represent these

objects and their properties, and also creating a class

hie-rarchy using inheritance and polymorphism Students

were required to design the objects an UML class diagram

with explanatory texts

• Lab week 3: a sample class hierarchy design was

provided Each group was required to compare this

sam-ple design with their own design, comment on

weak-nesses, strengths and trade-offs, and then revise their own

design

• Lab week 4: each group was required review its solution

in terms of “the evil of duplication”, meaning each group

had to check and identify duplication of code in creating

objects and in parsing objects’ properties, and then update

their design to resolve duplications All groups were

re-quired to submit their final solutions

C Participants and Procedure

A class for the OOP course with 48 second-year students

majoring in computer science was chosen to conduct the

experiment Each student was ranked by his or her previous

achievements (e.g., grades in earlier semesters) and

perfor-mance in an individual pre-test The students were then paired

using their capability ranks to making sure that two students

on each group have similar capability We ended up with 5

levels, naming between A and E, to group the students

1http://www.w3.org/TR/SVG11/

Groups in the same rank are considered equally competent Rank A has 3 groups, B with 2, C with 6, D with 8, and E with

5 groups

Pre-test An individual pre-test was conducted prior to the

project to check students by their understanding of basic introductory materials The pre-test scores were used in part to rank and group students, as described above

Tools and setup The system was put online at

https://ideol.net for access at any time For each group an online project was created with the two members and one instructor Most of students had been exposed to the system in our earlier IDEOL experiments [1] We asked those who were not familiar with the system to explore and use it prior to the experiment

Weekly tasks and lab sessions Each week’s tasks were

given a few days before the lab session Students could discuss with their instructor online through the system The instructors gave brief comments on previous groups’ submis-sions when posting new materials each week There were 4 weekly submissions during the experiment

Post-tests Students and groups were required to complete

individual and group post-tests Students were asked to demonstrate their knowledge and skills by working in the tests individually (for individual post-test) and in their groups (for group post-test) The individual post-test included theoretical questions while the group post-test did not

Survey and feedback After the experiment, students were

asked to complete a 7-point Likert scale survey and an open feedback form These questionnaires are used to gain informa-tion about student learning satisfacinforma-tion and students’ com-ments on the scenario-based project and IDEOL

D Metrics

The independent variables measure two types of data, the time spent and participation via the system These independent variables, which are described in detail below, include the time spent on the system by each student, communicating participation, and working participation

Time spent on the system (ToS) In general, this is the

amount of time that a student uses the system, excluding idle

time Idle time is identified as non-working time when there is

completely no activity in a period that lasts more than 2 minutes

Communicating participation (PC) measures the degree

of communication and collaboration between students and instructors through the system This measure is the weighted sum of communicating activities

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Fig 3 Distribution of Activities

PC = ™ Count of activities by type × Weight of activity type (1)

Activities considered as communicating participation

include creating a status or discussion thread (CC), updating a

thread status, e.g., from ‘unsolved’ to ‘solved’ (CU), reading a

status or thread (CV), posting a comment on a thread (CP),

and rating a thread or comment (CR) The type-weight pairs

are respectively (CC,1), (CU,1), (CV,1), (CP,2), and (CR,1)

The weight of activity type is based on the level of

contribu-tion and the effort required to perform activities of the type

The activity of posting a comment on a thread (CP) is

assigned the weight of 2 while the weight of the other

activities is assigned 1 because it requires at least twice as

much the contribution and effort as the other activities

As this metric only includes activities by students, the

count excludes instructors’ activities

Working participation or programming participation

(PW) measures the participation of students by counting

student’s programming activities performed on materials (e.g.,

the source code files and other project files) These activities

include opening the project, creating a file, changing a file

content, opening a file for reading, removing a file, starting a

build session, starting an execution (program running) session,

and starting a debug session All these activities are equally

weighted

The dependent variables measure student learning scores

and learning satisfaction The student learning scores are the

post-test scores achieved by individual students at the end of the project

Learning satisfaction is measured using 7-point Likert scale questionnaire consisting of question items on the system and the project with interactions between students and instructors Each question is rated on a scale from 1 or “strongly disagree”

to 7 or “strongly agree”; and the middle rating scale is 4, meaning “neither disagree nor agree” These questions were based on learning effectiveness satisfaction suggested by Sun and Cheng [9] and end-user satisfaction by Doll and Torkza-deh [10] and Davis [18] Examples below are two questions

on the system and the project, respectively

“The project design helped me learn easier”

“Using IDEOL was an enjoyable experience for me”

IV RESULTS

All activities performed on the IDEOL user interface were recorded automatically by the system Using the activity type for identification, we computed the values of ToS, PW, and

PC metrics Many activities such as mouse clicks and key presses were not counted, but they were used to identify time spent on the system and whether a session is active

All except one of 24 groups participating in the project completed and submitted work required for each week This group did not participate in the fourth week and did not complete the final submission, and its group members did not

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use the system much for compiling, running, and debugging

source code Thus, we excluded this group and their members

from the analysis In addition, two of 48 students did not

complete the individual post-test required Because of the

importance of the post-test score, they and their corresponding

groups were not included in the analysis in this section The

remaining data, which was collected from 42 students and 21

two-member groups, was used for analysis

We measured the participation of students on the project

using three metrics, time spent on the system (ToS), working

participation (PW), and communicating participation (PC)

ToS was determined by totaling the time between activities

excluding the idle time that was longer than 2 minutes PW

was measured by counting programming activities, such as

editing, compiling, running and debugging, that students

performed on their source code PC was a count of

communi-cation activities, and computed using the formula (1) above

A Working and Communicating Profiles

Fig 3 shows the distribution of activities performed by

students on the system, with the y-axis representing the time

spent on the system (ToS) measured in minutes, working

participation (PW) and communicating participation (PC)

activity counts and the x-axis representing the days during the

4-week project This distribution represents time, working,

and communicating profiles of all students in completing the

project The project has four weekly submissions at Days 7,

14, 21, and final submission at Day 28 As shown in the

figure, the trends for ToS and PW are quite similar The ToS

and PW values increase sharply in each of these submission

days, meaning that students tend to do more programming

work on these days A closer look at the data, we found that

13 out of 21 groups spent 30% or more of their total project

time on the submission days, with one group spending 2/3 of

their total project time on the these days

The PC trend is rather different with PW’s as students did

more communication, e.g., posting and reading comments and

threads, in a few days prior to the submission day Comparing

the PC and PW trends, we can see that students tend to

communicate across the weeks while they work on

program-ming more on the submission days

The profiles also indicate that few activities were taken on

the first two to three days following each of the submission

days although the requirements for the next submission were

already available on those days

The project did not require students to do much

program-ming in the first week, but required students to design and

create UML diagrams for the project The profiles, however,

show moderate programming and collaborating activities It is

possible that students tried to explore and learn the functional-ity of the system The work on the second week was signifi-cantly higher than the rest, which reflects the week’s require-ments with asking students to create classes, their properties, and relationships among them Other than this week, the workload seems to be balanced among the weeks

B Student Learning Satisfaction

Data on learning satisfaction was collected via the ques-tionnaire consisting of 30 questions that were divided into two main categories, project satisfaction and IDEOL system satisfaction with 15 questions each The project satisfaction questions were used to measure students’ experiences on the schedule, design, and execution of the project The system satisfaction questions focused on how students thought about the IDEOL system, such as its utility, quality, ease of use, friendliness, and efficiency

Of 30 questions in the questionnaire, there were six ques-tions asking students about their experience in collaboration and interaction with their group members and instructors through the project execution and the system These questions asked whether students received sufficient information on time, whether the system allowed them to collaborate easily, whether they were overall satisfied with the teamwork and collaboration with other students and instructors We call this

category of questions collaboration satisfaction

TABLE I A VERAGE V ALUES OF L EARNING S ATISFACTION

Table I shows the average levels of overall learning satis-faction and its subcategories, satissatis-faction on the project, on the system, and on collaboration All of these levels are

statistical-ly significantstatistical-ly greater than the average level of 4.0 “neither

disagree nor agree” (Student’s One-Sample T-test, p = 0.00 <

0.05) In fact, all of the questions received the level of 4.0 or higher except two questions on the stability and quality of the system with both being rated the average score of 3.8 This score reflects the fact that the system sometimes crashed and Internet connections were slow and not stable during the project

Comparing the satisfaction levels of the categories, we found that the project satisfaction levels are statistically greater than those of system satisfaction (Student’s

Two-Sample T-test, p = 0.00 < 0.05) and collaboration satisfaction

(p = 0.01 < 0.05) This result implies that students were more

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satisfied with the project design and execution than with the

IDEOL system and collaboration via the system The

satisfac-tion levels of overall learning, system, and collaborasatisfac-tion are

not statistically different although the average satisfaction

level of collaboration is higher than that of the system

V DISCUSSIONS

In this section, we present discussions on the results shown

in the preceding sections by addressing the research questions

and providing our interpretations of the results as well as the

limitations of the study

RQ1: Given the exercise that requires them to submit

work frequently, how often do students communicate and

do programming work on IDEOL?

To address this question, we generated the student

pro-gramming and communicating profiles by presenting counts

of student programming and communicating activities

throughout four weeks of the project (see Fig 3)

The project spanned in four weeks which each has a

sub-mission at the end of the week Although students work on the

project throughout the days of four weeks, they only spent a

significant amount of time on the system and performed many

programming activities at each of the submission days

Students also did little work on the first few days following

the submission date

The profiles show that students tend to postpone their

programming work until the due date While this academic

procrastination is not new in educational literature (e.g., [11]),

the profiles provide insights into the procrastination

phenome-non in the context of programming exercises From the

profiles, we recommend that the extended programming

exercise should be designed to include frequent deadlines that

are distributed across the timeline This design requires

students to better do the programming work ahead of the final

submission, and helps avoid the case where students made bad

estimates and do not have enough time to complete the

programming exercises

During the execution of programming exercises, the data

captured by IDEOL provides us useful information to make

corrective actions to balance workload for students and

instructors throughout the course duration Instructors should

adjust the exercise requirements and schedule when the

workload reported by the system is too low or too high In this

regard, IDEOL becomes a tool to not only report actual time

and activities performed but also to gauge and monitor

students’ workload

RQ2: How much are students satisfied with the design

of the project, the IDEOL system, and collaboration?

We addressed this question through a survey of students at the end of the project The survey asked students to rate their levels of satisfaction on the design and execution of the project (project satisfaction), the functionality and characteris-tics of IDEOL (system satisfaction), and the collaboration experience using IDEOL

The results shown in Section IV.B indicate that students were overall satisfied with the whole learning experience They were more satisfied with the project design and execu-tion than the IDEOL system Examining further the survey result, we found that students found the system to be unstable and slow Internet connections causing frequent disconnections during their work Moreover, the system’s functionality was quite limited with lack of powerful capability of a typical desktop-based IDE such as real-time error feedback, code completion, and stack trace

Although many of such limitations can be resolved in future versions of IDEOL, it is almost impossible to replicate powerful capabilities of popular desktop-based systems such Eclipse and Visual Studio because of limitations of the Web environment

Students also rated high on their collaboration experience They found that the system allowed them to collaborate with the peer and instructors easily (satisfaction score = 5.1), and information concerning the project was provided on time (satisfaction score = 5.1)

VI THREATS TO VALIDITY

The study has several limitations that may present viable threats to validity of our results

One concern is that the time and activities captured by IDEOL only reflect just a portion of all actual work done by students on the project We provided students IDEOL to collaborate and program the OOP exercise, but we did not prevent students from using other tools for collaboration While this design reflects the reality, using other more powerful programming tools or popular channels of commu-nication besides IDEOL might alter overall student expe-rience, and thus, affect student satisfaction Students could have used more powerful but less interactive IDEs such as Eclipse and Visual Studio to program and then pasted the source code to IDEOL Moreover, there are many activities that can be performed outside IDEOL such as face-to-face discussion, brainstorming, and drafting solutions on paper From IDEOL, we could not completely detect such activities from students who participated in the exercise Nonetheless,

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the large number of programming activities taken by students

throughout the project via the system leads us to believe that a

meaningful portion of work was done using the system, and

thus, it is well reflected in the data used for the analysis

The second possible threat to validity is that the idle time

was set to 2 minutes, which affected the calculation of time

spent on the system If a session was idle for more than 2

minutes, we considered that the corresponding student left the

system and was no longer working on the exercise However,

this assumption may not be true if during this period, the

student still worked on the exercise except that he was

thinking or working on paper This is a limitation of the

current IDEOL, which will be investigated in future

enhance-ments of the system

VII CONCLUSIONS

This paper reported our study in designing and executing

the programming project in our introductory OOP course

using IDEOL The project was performed by each of 24

two-member groups in four weeks All communication and

programming activities, project requirements, design

docu-ments, source code, other materials, and submissions were

captured by IDEOL

This study reported several interesting results The data

captured in IDEOL shows that students tend to postpone their

programming work until the submission dates, which confirms

the academic procrastination phenomenon known in

educa-tional literature To cope with this phenomenon in

ming exercises, this study suggests that an extended

program-ing exercise should include multiple deadlines to distribute

work during the project IDEOL offers instructors capabilities

to monitor and report students’ workload so that project

assignments can be adjusted accordingly Moreover, this study

provides an approach to designing and executing an extended

programming exercise which uses IDEOL for both

program-ming and facilitating collaboration among students and

instructors Through a series of submission deadlines, the

project requires students to plan their work effectively and

thus helps them avoid overloading Additionally, our survey

showed high student satisfaction with the design and

execu-tion of the programming exercise and the collaboraexecu-tion

experience via IDEOL Students found easy to share resources

and interact with peers and instructors via the system

Although the study has several limitations as we described

in the previous section, it suggests several implications First,

a collaborative Web-based like IDEOL offers a useful

integrated set of features for programming exercises in

programming language courses It allows online

collabora-tions and interaccollabora-tions between students and instructors to be

taken easily while providing programming capabilities for students to learn and practice programming Via the system, students and instructors can share resources, ideas, and information about the programming exercises Students on the same team can work on the same programming tasks at the same time and make consensus decisions about what and how

to do When having issues or unsure how to do, students can post their questions or concerns on the embedded discussion board, and other students or instructors can provide feedback instantly or at a later time Instead of using various disinte-grated tools for interacting, programming, and storing, students and instructors use the integrated IDEOL system for these purposes to have a consistent view of what they work

on Second, the system allows instructors and researchers to automatically capture data from collaborations, interactions, programming activities, team work, and other kinds of activities performed on the system Such data is useful for improving teaching and student learning experience and for verifying learning and teaching approaches

We plan to apply the system to experiment and evaluate the effectiveness of different team settings in programming assignments We will also investigate the effects of virtual social network interactions on students’ performance, satisfaction, and involvement in programming courses

This work is supported by Vietnam National University –

Ho Chi Minh City (VNU-HCMC) under Grant No B2013-18-01

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