Implementing a Large On-Campus ALN: Faculty Perspective
Edwin Kashy, Michael Thoennessen, Guy Albertelli II, Yihjia Tsai
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1
Michigan State University
1 Permanent Address: Department of Computer Science, Tamkang
University, Taiwan
Abstract
This case study describes the implementation and continued operation of
a large on-campus ALN for a 500-student course in introductory physics.
The ALN was used to modify and complement the original course and thus
represents an evolution rather than a revolution. A highly positive impact
on student success rates was achieved and continues. Factors that increased
faculty satisfaction and instances of dissatisfaction are presented. The
potential increase in the latter with technology is of some concern.
I. INTRODUCTION
Approximately 500 science and engineering students enter the calculus-based
Introductory Physics two-semester course, PHY183-184. For most of the
students in the class, this course is a requirement each semester. The
course is part of the established curriculum. Its goals and standards
are well defined by the textbooks commonly used across various institutions.
In its present form, it is an attempt to combine the best features of
the face-to-face interactions and lectures with the use of network tools
for anytime/anywhere interaction. The goal has been to establish and maintain
high standards while providing students with the means and opportunity
to succeed. This ALN was initiated in fall 1995 and has been continued
since that time [1].
II. RATIONALE
In fall 1995, we implemented our first ALN with support of the Sloan
Foundation. This was in large part as a consequence of discussion with
colleagues at UIUC who had embraced the ALN concept and already had encouraging
initial results [2]. Our ALN followed three years of computerized assignments
in introductory physics and chemistry courses using the Internet. This
showed the added dimension that networked technology could add to a course.
The prospect of improved student performance and satisfaction was also
a driving factor, especially as we had observed that students were spending
considerably more time in the course. For the first time, we were seeing
student effort at a level that justified our own instructing efforts.
This was indeed a source of satisfaction!
Other members of the department taught this course during the past two
years (Table 1). While using the ALN was not required, they were encouraged
to do so to take advantage of the savings that were generated by the reduced
teaching staff used in the ALN, i.e., about two-thirds of that in the
traditional course (The reduction of teaching staff results from the automated
grading with CAPA. Teaching assistants (TA) for grading are not needed
anymore. Instead a smaller number of TAs is used for face-to-face and
ALN help. The savings are proportional to the class size). The comments
of these instructors are included in this case study.
|
ID
|
Rank
|
Years
Teaching
|
Teaching Awards
|
IT Technology Experience
|
|
EK
|
Prof.
|
40
|
Yes
|
Yes
|
|
MT
|
Prof.
|
8
|
Yes
|
Yes
|
|
WL
|
Prof.
|
14
|
No
|
Some
|
|
BP
|
Prof.
|
22
|
No
|
Some
|
Table 1. Information About the Four Faculty Members of
this Study
III. BACKGROUND INFORMATION FOR THE COURSE
This course was the first to use essentially all the features of an on-campus
ALN. Being a required course for a large number of students, planned and
actual enrollment was the same, 480 students.
A coordinator provided the technological support for the 15-20 instructors
using the CAPA system each semester at Michigan State University (MSU).
This included obtaining class lists electronically and providing them
to the instructor in the proper format for immediate use, setting up the
class directories, and testing that the system was operational for student
login via the Web and/or Telnet. The coordinator also set up the Internet
discussion forum for students, initially with commercial software and
later as part of CAPA, and assisted in responding to students who encountered
difficulties related to the technology.
Instructor training was a key part of the technological support. At MSU,
supported by our Sloan Foundation grant, we have opted for one-on-one
training and it has worked very well so far. The coordinator introduces
the instructor to the system and works with the instructor on the technical
aspects of content preparation and operation. The learning curve is thus
very steep and de-facto adapted to the instructor's technological skill
levels. Time to become proficient enough to run a course has varied from
less than three hours to three days. For most of that time, however, the
instructor and coordinator are working on their own in the same office,
with any difficulty encountered being addressed immediately. While this
may appear to be less efficient than training in a class or workshop,
our success rate is total; once proficient, most instructors continue
to use the technology.
Note that E. Kashy and M. Thoennessen are part of the development team
of CAPA as an ALN tool. They had relatively small technology support requirements
for ongoing course tasks, but had support in testing and implementing
new or upgraded features.
A. Technology and Infrastructure
The principal ALN tool used was CAPA, a computer system developed at MSU
over the past seven years. In the initial experience with its use, a 90-student
science class, student reaction was very positive and has since been replicated
in numerous other disciplines and at other institutions [3-9]. This integrated
software system has been used to
- Prepare, deliver, and grade personalized homework, quizzes and examinations.
- Provide feedback to students and instructors.
- Communicate with students in a class and provide a discussion forum
for students.
- Provide links for student help via the Internet.
- Facilitate course management - Table 2 summarizes some of the CAPA
features for the instructor.
- The system was originally developed for Physics and Chemistry courses
[3,5] and was used to develop a broad variety of conceptual questions
adapted to the technology. Students are given several tries to get correct
solutions and are given full credit when they succeed before the due
date.
| 1. QUIZZER
Multifaceted editing tool for preparing homework, quizzes,
and examinations |
Prepares materials in three formats:
ASCII, HTML, LATEX |
| Each student receives unique questions
and problems |
| Over 170 pre-coded templates to facilitate
creation of questions |
| Allows printing of text and graphics
in a compact, efficient manner |
| Due dates can be set for individual
sections independently |
| Includes a timed entry option for
use with take-home quizzes and exams |
| A simple transformation allows conversion
from homework style to exam style |
| Provides the range of answers for
a question across all students in a class |
| Efficient assembly of existing problems
from problem libraries |
| 2. MANAGER
Course management and statistical analysis tools.
|
Provides distribution of grades for
an assignment |
| Instructor can examine number of
attempts made by students for each problem |
| Can analyze answer patterns to detect
misconceptions:
1. Correlations between items
2. Degree of discrimination
3. Degree of difficulty |
| Course summaries for individual students
can be generated for advising |
| Grades scantron forms when the pattern
of correct responses varies |
| Can send semi-personalized E-mail
to students based on performance |
| 3. GRADER
An additional grading tool that supplements self-grading by
students |
Allows instructor to grade subjective
answers such as essays |
| Provides answers for individual student's
assignments for hand-grading |
| Allows a problem to be excused for
an individual student, section, or class |
Table 2. The Three CAPA Modules Available for the Instructor
While hints are available when an incorrect answer is given, the system
does not attempt to give the students feedback on the particular error
made (other than a formatting error). We believe that a key aspect of
problem solving lies in the ability to both detect and correct one's mistake.
The strong emphasis on conceptual problems within CAPA makes it is a useful
tool for many fields [7,9,10]. Figure 1 shows an example of a conceptual
problem. It clearly goes beyond a traditional one-out-of-five multiple-choice
question. To solve this problem, students need a reasonable understanding
of Archimede's Principle.
|
[1pt] A fisherman and his young daughter
are in a boat on a small pond. Both are wearing life jackets.
The daughter is holding a large floating helium filled balloon
by a string.
Consider each action below independently,
and indicate whether the level of the water in the pond R-Rises,
F-Falls, S-Stays the Same, C-Can't tell. (If in the first the
level Rises, and in the second it Falls, and for the rest One
Cannot Tell, enter RFCCC.) |
|
A) The daughter
pops the balloon.
B) The fisherman knocks the tackle box overboard and it sinks
to the bottom.
C) The fisherman lowers himself in the water and floats on his
back.
D) The fisherman fills a glass with water from the pond and drinks
it.
E) The daughter gets in the water, looses her grip on the string,
letting the balloon escape upwards. |
Figure 1. Example of a Conceptual Question in CAPAThe
hint will read: "Think Archimede's Principle. How does the volume
of fluid displaced by a body that `floats' differ from that for a body
that sinks?"
An additional strength of CAPA is the variations of a problem among students.
A simple example is shown in Figure 2. Two versions of the same problem
are shown for different students. This encourages collaboration without
simply copying the solutions. Again, each individual student has to understand
his own problem. It is also possible to give the students different selections;
however, one should be careful that all the same concepts are presented
to all students.
| 2. [1pt] John is listening to
a horn. He knows the frequency of the horn is 300 Hz when both
he and the horn are at rest. If he hears a pitch of 270 Hz, there
are clearly several possibilities.
(Give ALL correct answers, i.e., B, AC, BCD...) |
2. [1pt] Paul is listening to
a horn. He knows the frequency of the horn is 300 Hz when both
he and the horn are at rest. If he hears a pitch of 330 Hz, there
are clearly several possibilities.
(Give ALL correct answers, i.e., B, AC, BCD...) |
| A) Both can be moving and have the
same speed.
B) Both can be moving, in opposite directions.
C) The distance between John and the horn is decreasing with
time.
D) John is moving away from the horn at rest.
E) Both can be moving and have different speeds.
F) Both cannot be moving in the same direction. |
A) Both can be moving, in opposite
directions.
B) Both can be moving and have the same speed.
C) Both can be moving and have different speeds.
D) Paul is moving towards the horn at rest.
E) The distance between Paul and the horn is increasing with
time.
F) Both cannot be moving in the same direction. |
Figure 2. Two Different Versions of the Same Problem
The selections are automatically randomized.
Conceptual problems are an important part for understanding.
There is a large correlation between understanding the concepts and the
ability to solve numerical questions as shown in Figure 3.

Figure 3. Correlation Between Conceptual and Numerical Problems
The most recent addition is a direct link to a discussion forum implemented
in CAPA when accessing from the Web. This allows each student to participate
directly in a discussion with other students and/or the teaching assistant
(TA) while working on a specific problem. This feature simplifies the
use of discussion groups significantly because the additional log-in and
password required for an external discussion forum is not necessary. In
this moderated discussion forum, the TAs make sure that the postings are
hints and not just the posting of formulas. This control mechanism does
not exist for Websites initiated by students that have recently appeared.
On these sites solutions are posted and even problems having typical randomized
variables can have their solutions posted. Fortunately, these student
endeavors can be overcome. Figure 4 shows an example we have used. As
can be seen it is virtually impossible to communicate the solution of
this problem over the Web without discussing the physics involved (Kirchoff's
Rules). That is exactly the purpose of collaboration-explaining and understanding
the problems. It becomes easier to learn how to do the problem than to
subvert the system.

Figure 4. Additional Randomization of Labels with CAPA
B. Content Delivery
Table 3 shows the various components of the course. As in most physics
courses, demonstrations are a large component of lecture time. Traditional
lecture time is, however, significantly reduced, allowing for large segments
of time on interactive lecture exercises and unannounced short quizzes.
These quizzes have had a positive impact in improving class attendance
even though they serve to assign only a small proportion of the student's
grade (5%). The quizzes are also useful in identifying misconceptions
very early.
Homework assignments are personalized. The conceptual problems are designed
to encourage collaboration among students as they can benefit from the
additional practice of working on somewhat different versions of the same
problems. Numerical story problems have variables that inhibit rote copying
among students. Recently we have added new techniques that have strongly
inhibited the sharing of formulas where one can just plug in one's variables
and get the correct answer without really understanding the problems.
Each weekly assignment has a firm due date. This insures students do not
fall behind. Students are given full credit if they get the correct answers
before the due date. If a solution entered is incorrect, the student may
work to find the errors. A number of attempts are allowed to obtain the
solution. Thus, most students are able to receive very good grades on
the assignments, and this has proved to be highly motivating. Note that
these high grades do not lead to grade inflation, as a higher absolute
scale is used to assign the course grade.
| Activity |
Before (%)
|
Current (%)
|
| In-class Time: |
|
|
| Lecturing |
70 |
40 |
| Quizzes |
5 |
15 |
| Exercises |
5 |
25 |
| Demonstrations
|
20 |
20 |
| |
|
|
| Recitation Time |
100 |
0 |
| Learning Center (Face-to-face) |
0 |
100 |
| Discussion Forum |
0 |
100 |
| Feedback |
20 |
80 |
| Exam Corrections |
0 |
100 |
Table 3. Time (%) Spent on Various Aspects of the Course
Collaboration is also encouraged by a small component of
teamwork in assignments. For example, groups of up to five students working
together can submit a subjective essay discussing the observation of an
experiment shown by video during class. This also has a big efficiency
factor for the instructor grading these essays.
Assignments have a significant component of challenging problems. Students
can obtain help at any time via the discussion forum established for the
class. Posted questions are sure to be addressed within 24 hours or less
by TAs or other students. In addition, help is available at scheduled
periods throughout the week in a Physics Learning Center. There teaching
assistants, who are assigned to the class and who have themselves solved
their own personalized assignments, use the Socratic method in helping
students with any difficulties. Students needing help can be there several
hours while those who do not feel such a need are not required to be there
at all. This face-to-face help is an important part of the class, especially
for less prepared students. It is also helpful to the instructor as it
provides complimentary feedback to the detailed on-line feedback available
from the student performance as recorded by the system. The Learning Center
is also the way we have countered the impersonal nature of instruction
in this large course. It provides many opportunities for one-on-one interactions
between students and teaching staff.
A concept test given during the first week and again near the end of the
class helps compare the class to others at similar institutions and represents
one of the measures of learning. Mid-term and final exams are the main
assessment tools. In the case of the mid-terms, we allow students to earn
partial credit by correcting any part of the exams on which they have
not done well.
Following the proctored examinations, students can pick up a copy of a
different version of the same exam. They then can solve the problems in
that version within the next three days and enter answers via the Internet.
They can consult with fellow students, the teaching staff, etc. to get
help. By this process, the mid-term grade is the original grade plus 30%
of the difference between the corrections and original exams, i.e., they
recover "30 cents on the dollar" of every missed point. More
than 99% of students avail themselves of this correction opportunity.
It is a very popular option! For the instructor, it represents an effective
and efficient way to encourage students to review all the material on
the exam and improve their understanding. (A common comment by students
finding out how to solve a problem missed on the exam is, "I should
have gotten it! It wasn't that hard.")
The 99% of the students who work on the corrections actually solve all
exam questions. In contrast, in traditional exams the students typically
do not even look at their wrong answers and do not try to understand what
they did wrong. This extra effort on the students' part comes at almost
no extra effort by the instructor.
III. RESULTS
A. Effectiveness
Before we discuss faculty satisfaction, we need to mention briefly the
effectiveness results obtained from our on-campus ALN approach. These
can be found in the Journal of Engineering Education [1], where we demonstrated
a strong, positive impact on student success in large classes while maintaining
high standards. In retrospect, the improvement in student achievement
observed should not have been surprising as our approach has been to retain
the best established practices of more traditional teaching and to use
ALN to fix the weak areas where it clearly can have a major impact.
The important aspects of using the technology which appear to have a significant
positive impact on student achievement include
- Interaction between the students and the computer using materials
and problems well adapted to the technology enables students to receive
instant feedback [11,12] on their understanding of concepts and ability
to carry out calculations properly. Concurrently, it provides access
to specific help provided by an instructor or provided via links.
- Interaction between the instructor and the computer provides the
instructor with on-line feedback on student misconceptions and misunderstanding
so that they can be addressed in a timely manner, usually before the
work is due. It provides early, comprehensive information about individual
students who are having difficulties. This information is essential
to properly advising these students.
- Asynchronous interactions among students and between students and
instructors via the network provide the opportunity for questions, answers,
discussions, and elucidation of difficult concepts within the context
of anytime/anywhere.
In addition, the efficiencies generated by the use of technology
allow us to devote increased teaching staff time to Socratic one-on-one
interactions with students.
B. Saving Paper
One issue in implementing the technology for large on-campus ALN course
involves the printing of personalized assignments. Since the assigned
work is on the Web, should students be given printed copies? Our
reason for printing and handing out assignments has been to promote an
environment where students collaborate and discuss their work. Such collaboration
has been shown to have positive impact on performance [13]. Would such
collaborations be less likely if they had to work at individual computers?
We have recently collected some data on the printing issue. In fall 1998,
assignments for a large student course (not using CAPA) were provided
on the Web. When polled, most of those students said they printed assignments
from the Web all or most of the time.
We then polled the students in PHY183 (480 students using CAPA) during
the fourth week of the semester to see if they would agree to have the
following week's assignment not printed. The vote was overwhelmingly against,
420 to 6. In addition, 89 students commented by E-mail-one was willing,
88 were not. The reasons given in those 88 E-mails are shown in Table
4.
| Why
students want printed assignments |
| Harder to work in front of screen
|
56% |
| Printed HW more accessible |
43% |
| Trouble printing from the Web, and
excellent quality of LaTeX printout |
27% |
| Web access required |
18% |
| Work on-line too long |
11% |
| Other reasons |
18% |
Table 4. E-mail Responses of 88 Students
We believe that in our situation, the small effort by the
instructor to prepare printed worksheets is well repaid by the large saving
in student time and increased student interaction level. Note that because
of a highly efficient format, our printing of the assignments prepared
with Latex requires from four to nine times less paper than when students
print from the Web.
C. Faculty Satisfaction
To put the faculty satisfaction issues in perspective, we have interviewed
faculty, including some who have not used ALN in their disciplines and
looked at previous studies of issues that affect faculty satisfaction
[14-19]. Faculty satisfaction is complex. The principal factors, which
emerge from the literature, from interviews with our colleagues in this
study, and from our own experience, include collegiality, workload, and
autonomy. An interesting observation concerns the role conflict that occurs
at the intersection between faculty and administrative domains of responsibility.
While it does not appear to affect general faculty satisfaction, it can
be a source of disaffection and dissatisfaction.
Our experience has been that the implementation of ALN technology on a
large scale in teaching has greatly increased the domain where administrative
and academic responsibility and control intersect. Thus, it is not surprising
that we have experienced numerous situations that engendered faculty dissatisfaction,
ranging from not so important to instances that, in our perception, are
critical factors in how we want to do our task. In this area of collective
decision-making and responsibility, we have encountered a spectrum of
administrative attitudes across the administrative ladder. In the four
situations briefly described below, we should keep in mind that the descriptions
are from the faculty and that the perception of the administrator(s) involved
may be considerably at odds. The following paraphrase professors either
using or using and developing ALN:
- Case A - While teaching a large (700 students) introductory
physics course, I came across a software program that displayed physics
demonstrations. This software was priced around $150. I had already
been displaying demonstrations on a screen and thought this software
would fit nicely with the existing format of the class. In response
to my E-mail requesting authorization to purchase that software, the
department chair responded that I should E-mail the person in charge
of the academic affairs committee, which I did. This person responded
that I should first get a demonstration version of the program, which
I did. I received the demonstration version of that program but that
version was inadequate. By this time, it was near the end of the term.
I was frustrated with the process and discontinued my attempt to incorporate
this program into my class.
- Case B - In implementing the large ALN on campus, I decided
there was a need to provide students an opportunity for a face-to-face
interaction and help with teaching staff above and beyond what was provided
through the network. A learning center was established with furnishings
consisting of tables and chairs and computers obtained from salvage.
The computer needs in this spartan environment were quite modest, vt100
terminal emulation, as our ALN predated the use of the sophisticated
Web browsers that are ubiquitously in use today.
As the use of the ALN concept spread to a greater number of students,
this initial setup soon became insufficient for the large demand and
new capabilities. Requests that the area be upgraded and improved in
several aspects eventually received administrative approval, at which
time I informed my students to bear with us for a bit as significant
changes were soon forthcoming in improving that component of the learning
environment. These changes were then canceled and not implemented until
more that a year later. I felt angry and frustrated.
- Case C - Discussion with the Dean and Chair established the
need for centralized support for faculty using the technology. The yearly
combination of contributions from the two most highly involved departments
and the College with miscellaneous funds (education research grant,
etc.) has provided a salary for a coordinator to support faculty across
campus in the use of the CAPA as ALN tool. Administration has clearly
expressed support of a more permanent arrangement, which would eliminate
my task to see that the support for the position is there each year.
In spite of the 6000+ students involved each semester, such an arrangement
is still not in place five years after the position was first filled.
- Case D - When a key developer of the CAPA system left the
University, I made repeated requests for support to continue development
and essentially met no action, either positive or negative. I then addressed
the request directly to the highest administrative level. This action
triggered a significant dissatisfaction at lower administrative levels.
Still, the outcome was that the request was fulfilled, with the University
continuing to support the system development.
For the present survey we explicitly interviewed six physics
professor who taught with CAPA recently. We also have close contact with
most of the instructors using CAPA for about 20 courses in several disciplines
on campus. The four cases above represent the major conflicts brought
to our attention. Note that they are one-sided views in areas of shared
responsibility and could be described in quite different terms from an
administrative perspective. In the implementation of ALN technology, such
areas have grown significantly, and thus, increase potential conflicts
as faculty and administrators carry out their tasks.
With the increased use of technology in education, administrators have
an increasing and important role in an area where they have limited knowledge
and in which faculty also are not often experts. A quote (with a large
dose of sarcasm) from a colleague asked to comment on sources of dissatisfaction
in his work, "... too much administrative interference, decisions
based on ignorance." We do not want to leave the impression
that conflicts dominate our interaction with administrators. On balance,
they have been facilitators and helped to establish the conditions in
which we have obtained highly positive and encouraging results [1].
The level of satisfaction with the on-campus ALN implementation is high
across many disciplines and faculty who have implemented all or part of
its functionality. This satisfaction comes in spite of the universal agreement
among faculty that work is increased, especially initially. Technical
support is rated good to "... wonderful." Positive interactions
with satisfied students, by far the majority, is a big factor, as is the
interactions with colleagues doing ALN with whom one can share a remarkable
variety of wonderful stories. The on-campus aspect has strong appeal.
One faculty who volunteered that he is now ".. a convert to this
technology" added that he liked that he was "still teaching
the normal way." Another commented, "This was the first
time I had the ability to really see how students were doing in such a
large course and could review that information before meeting with them."
There has been a redistribution of responsibility in the large courses.
There is some loss of faculty control as courses depend more on the support
of system administrators and on the proper functioning of the technology
infrastructure. More of the course administration and management has become
part of the lecturer's work. Instructors now have detailed knowledge of
student performance, and so do the students. There is far greater interaction
with students, via E-mail in particular, which is yet another factor increasing
the time spent on a course. Those students who are having a difficult
time, or who believe that getting some work excused is equivalent to having
done the work, take up a far greater proportion of the instructor's time.
Some students seek assistance when it is clear that very little studying
has occurred. This additional work is a source of dissatisfaction for
many faculty. Others who perceive the added work are not interested in
adopting the new technology.
For faculty excited by the new opportunities, there have been many rewards.
These include
- Increased collegiality with colleagues in other departments and disciplines.
- A perception that they can influence outcome.
- Improved relations with students who are benefiting and who view
the instructor as mentor rather than judge.
- Positive feedback from graduate assistants whose work has been moved
from grading and record keeping to Socratic interactions with students.
IV. SUMMARY
We believe that at MSU, ALN can and soon will be a significant
part of the educational experience for a majority of students. This will
be helped considerably if, as the number and variety of more sophisticated
technical tools become available, faculty are assisted in becoming skilled
in their use and the increased workload is kept in check. Broad implementation
will also be assisted if faculty and administrators develop means to deal
with the increasing number of conflict situations where their functions
overlap.
ACKNOWLEDGEMENTS
We would like to thank Professors W. Lynch, B. Pope, T.
Glasmacher and B. Sherrill for the participation and/or comments related
to faculty satisfaction. We also appreciate the help of N. Davis during
this project. Last but not least, support from the Sloan Foundation has
played a key role: it represented an external evaluation of quality and
provided resources that allowed us to quickly and broadly implement and
experiment with the new network tools.
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ABOUT THE AUTHORS
Edwin Kashy is a University Distinguished Professor
at Michigan State University in the Department of Physics and Astronomy.
He earned his Ph.D. in Nuclear Physics from Rice University in 1959. He
was an NSF post-doctoral fellow at MIT, and then served there as an instructor
until 1962. He then joined the faculty as an assistant professor at Princeton
University before joining the faculty at MSU as associate professor in
1964. His research areas have been in spectroscopy, Coulomb effects and
temperature in atomic nuclei. Since 1992, he has been using technology
in his classes and has led the teams at MSU who have developed the networked
CAPA (Computer Assisted Personalized Approach) system. He has been assessing
the impact of technology in teaching, currently with support from the
Alfred P. Sloan and Andrew W. Mellon foundations. Dr Kashy's honors include
the John Simon Guggenheim Fellowship, the Distinguished Faculty Award
at MSU and the Excellence in Physics Teaching Award; he is also a past
CASE Professor of the Year nominee. The work he has done with his colleague
on the impact of technology in teaching has been recognized by the ASEE
Benjamin J. Dasher Award (98) and the William Elgin Wickenden Award (99).
Contact: Department of Physics and Astronomy, College of Natural
Science, Michigan State University, East Lansing, Michigan 48824; Telephone:
517-333-6318; Fax: 517-353-5967; E-mail: kashy@nscl.msu.edu.
Michael Thoennessen is a Professor of Physics at Michigan State
University in the Dept. of Physics and Astronomy with an appointment at
the National Superconducting Cyclotron Laboratory. He earned his Ph.D.
in Experimental Nuclear Physics in 1988 at the State University of New
York at Stony Brook. His main research is in nuclear physics where he
studies nuclei far from stability. He has been using technology in teaching
his classes since 1994, and has been a member of the CAPA development
team. His honors include the Outstanding Mentor Award ('94), the T.H.
Osgood Award for Teaching Excellence ('95), the Teacher Scholar Award
for the College of Natural Science ('96), and the Physics department Outreach
Award for his leadership of the Research Experience for Undergraduates
program. He is also co-awardee of the ASEE Benjamin J. Dasher Award ('98)
and the William Elgin Wickenden Award ('99). His research also include
assessment of learning with technology with support from the Alfred P.
Sloan and Andrew W. Mellon foundations.
Contact: Department of Physics and Astronomy, College of Natural
Science, Michigan State University, East Lansing, Michigan 48824; Telephone:
517-333-6323, Fax: 517-353-5967; E-mail: thoennessen@nscl.msu.edu.
Guy Albertelli is currently a Specialist in Educational Technology
at Michigan State University. He received his B.A. in Computer Science
at Michigan State University in 1996 and his M.S. in Computer Science
from Ohio State University in 1997. He first joined the CAPA development
team while an undergraduate student at MSU, contributing the first computer-scored
software for optically scanned individualized examinations. Since 1998,
He has been the lead programmer and developer for CAPA and his work has
resulted in a much more user-friendly system. His current project is the
Development of a new ALN tool: LON-CAPA (Learning OnLine Network with
a Computer Assisted Personalized Approach). His research also includes
assessment of learning with technology with support Andrew W. Mellon foundations.
Contact: College of Natural Science, Michigan State University,
East Lansing, Michigan 48824; Telephone: 517-432-5652, Fax: 517-353-5967;
E-mail: albertel@pilot.msu.edu.
Yihjia Tsai is currently an Assistant Professor of Computer Science
and Information Engineering at Tamkang University in Taiwan, and has been
a visiting scholar at MSU for several periods from 1998-2000. He received
a B.S. in Mechanical Engineering from the Taiwan National University in
1985. Following a period of work in industry, he earned a M.S. (1995)
and Ph.D. (1997) from Michigan State University. He was a member of the
initial CAPA development team, was the principal programmer from its inception
until 1998, and is actively participating in its current development.
His research interests include fundamental aspects of communications in
computers, as well as the use of computer technology in education. He
is also co-awardee of the ASEE Benjamin J. Dasher Award ('98) and the
William Elgin Wickenden Award ('99).
Contact: Computer Science and Information Engineering, Tamkang
University, Taiwan; E-mail: tsai@cs.tku.edu.tw.
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