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An Alternative Theoretical Framework to Analyze Failures in Decision Making: Application to Student Dropout in Asynchronous Learning Environments Naj Shaik PhD [email protected] University of Illinois at Urbana-Champaign Ninth Sloan-C International Conference on Asynchronous Learning Networks

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An Alternative Theoretical Framework to Analyze Failures in Decision Making: Application to Student Dropout in Asynchronous Learning Environments

Naj Shaik PhD

[email protected]

University of Illinois at Urbana-Champaign

Ninth Sloan-C International Conference on Asynchronous Learning Networks

Nov 14-16, 2003


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  • Student dropout is rarely the result of a single point of decision failure but typically occur when the system breaks down at multiple points along the chain

    • Adapted from James Reason. Human Error. Cambridge University Press, 1990.

  • Retention is everybody's business

    • Provost, Virginia Commonwealth University


Retention rates l.jpg
Retention Rates decision failure but typically occur when the system breaks down at multiple points along the chain

Historical Data

  • Between 1880 & 1980 the rate of retention in US was around 55% (Tinto, 1982) which is higher than Australia and UK.

    Current Research

  • Traditional Students: Second year retention rate

    • 80% for member institutions, 87% for selective institutions and 69% for less selective institutions (Consortium for Student Retention Data Exchange 2001).

    • 74% for private and 72% for public 4-year institutions (ACT 2001).

  • Non-Traditional Students: Second year retention rate

    • Retention rates for distance education programs are lower than those for the traditional on-campus programs and courses (Dutton, Dutton, and Perry, 2001; Terry, 2001; Carr, 2000).


Significance of retention issue l.jpg
Significance of Retention Issue decision failure but typically occur when the system breaks down at multiple points along the chain

  • A number of federal and state agencies request the reporting of retention data.

  • U.S. Department of Education plans to emphasize raising retention rates in higher education while working with Congress to reauthorize the Higher Education Act (reported in Chronicle of Higher Education, Dec 2002).

  • It is used as an indicator of academic quality in U.S. News and World Report annual college rankings (Graham and Morse, 1998).

  • A low retention rate reflect poorly on a program and impact program promotion and recruitment efforts.


Conventional theoretical models frameworks l.jpg
Conventional Theoretical Models / Frameworks decision failure but typically occur when the system breaks down at multiple points along the chain

  • Over the last 3-decades a number of frameworks have been proposed to explain the student dropout phenomena based on student behavior.

    • Sociological Model (SM): Spady

    • Student Integration Model (SIM): Tinto

    • Social & Personal Beliefs Model (SPBM): Fishbein & Azjen

    • Student Attrition Model (SAM): Bean

    • Integrated Retention Model (IRM): Cabrera et. al.

    • Congruence Model (CM): Boshier

    • Chain of Response Model (CRM): Cross

    • Identity Theory Model (ITM): Witte et al.

    • Composite Persistence Model (CPM): Rovai

    • Rational Choice Model (RCM): Manski & Wise


Student integration model sim l.jpg
Student Integration Model (SIM) decision failure but typically occur when the system breaks down at multiple points along the chain

Student Integration Model is based on

  • Durkheim (1951) theory of suicide

  • Van Gennep (1960) theory of rites of passage

  • Predictive version of Spady sociological model.

  • Individual pre-entry college attributes (family background, skill and ability, prior schooling) form individual goals and commitments.

  • The individual’s goals and commitments interact over time with institutional experiences (the formal and informal academic and social systems).

  • The extent to which the individual becomes academically and socially integrated into the academic and social systems of an institution over time determines the decision to dropout.

  • The absence of successful integration arises due to incongruence (odds with the institution) and isolation (disconnected from the institution).


  • Enhancements to student integration model l.jpg
    Enhancements to Student Integration Model decision failure but typically occur when the system breaks down at multiple points along the chain

    • Student Attrition Model (Bean): importance of external variables such as finances, family responsibility and support etc for non-traditional students.

    • Congruence Model (Boshier): Influence of environmental variables such as ….

    • Integrated Retention Model (Cabrera et al.): an integrated framework based on the overlapping factors between SIM (Tinto) & SAM (Bean).

    • Identity Theory (Witte et al.): non-traditional student’s identity development and its influence on student behavior.

    • Composite Persistence Model (Rovai): includes learning environment, nature of teaching and learning etc to the evolving framework.


    Synthesis conventional fit models l.jpg
    Synthesis: Conventional “Fit” Models decision failure but typically occur when the system breaks down at multiple points along the chain

    • Dropout is explained through student-institution “FIT" by looking at student, institutional, and environmental variables.

    • Absence of successful integration is attributed to incongruence (odds with the institution) and isolation (disconnected from the institution). (Tinto)

    • Student Responsibility: “ … either low goal commitment or low institutional commitment can lead to dropout.” (Tinto, 1976. p.96).


    Observations conventional fit models l.jpg
    Observations: Conventional “Fit” Models decision failure but typically occur when the system breaks down at multiple points along the chain

    • Incongruence: “… students must disassociate … from membership in the communities of the past, [such as] …. family, the local high school, [etc.] …(Tinto, 1987, p.95)” to become fully incorporated with the college community.

      • Implications: Students to “commit a form of cultural suicide to be academically successful” (Tierney, 1999, p.85).

    • Transition: The reference to theory of rights of passage is inconsistent with anthropological basis.

      • Rights of passage signifies movement within the same culture and not between cultures (Tierney 1992).

    • Integration / Fit appeals to commonsense but hides the complexity and over simplifies the issue (Draper, 2003).


    Observations conventional fit models10 l.jpg
    Observations: Conventional “Fit” Models decision failure but typically occur when the system breaks down at multiple points along the chain

    • Empirical Support (Draper, 2003)

      • Research is based on weakly consistent evidence.

      • No comparative research testing competing frameworks.

      • Absence of controlled experiments.

    • Absence of a psychometric-based standardized instrument for data collection.

    • Absence of standard protocols to administer instrument.

    • Generalization not possible due to data constraints.

    • In the absence of a common metrics valid time-series and cross-program comparisons on dropout rates are difficult to interpret (National Research Council, 1996).

    • The list of explanatory variables is growing as we look at the number of suggested enhancements to the ‘Fit’ framework.


    Alternative theoretical framework l.jpg
    Alternative Theoretical Framework decision failure but typically occur when the system breaks down at multiple points along the chain

    • Based on cognitive architecture and draws on the field of cognitive psychology particularly the contributions of

      • Rasmussen: Skills- Rules- & Knowledge Framework

      • Norman: Error Taxonomy

      • Reason: Generic Error Modeling System

    • The dropout phenomenon is described as attributed to divergent origins from technological failure to managerial oversight to organizational weakness.

    • The goal is to highlight the importance of organizational environment relative to individual performance.


    Rasmussen s step ladder framework l.jpg
    Rasmussen’s Step Ladder Framework decision failure but typically occur when the system breaks down at multiple points along the chain

    Interpretation Evaluation

    IdentificationGoal Selection

    ObservationProcedure Selection

    Problem  Activation  Execution Problem Solved

    • Represents constraints in the work environment.

    • Describes three levels of human behavior in terms of increasing order of cognitive processing.

    • Comprises a three level hierarchy defined by skilled-based, rule-based and knowledge-based behavior.

    • At the lower level actions are more specific and rigid while at the higher level actions are more general and flexible.


    Rasmussen s step ladder framework13 l.jpg
    Rasmussen’s Step Ladder Framework decision failure but typically occur when the system breaks down at multiple points along the chain

    • Skill-Based (SB) corresponds to effortless routine actions that take place as smooth, automated and highly integrated patterns of behavior (driving under normal weather conditions).

    • Rule-Based (RB) is applicable to tacking unfamiliar anticipated problems. Solutions to these problems are governed by stored rules which are learned by explicit training and by experience (driving on a slippery road).

    • Knowledge-Based (KB) is applicable to unfamiliar unanticipated problems. It requires reasoning to diagnose and solve problems, identify deep features about a situation, adapt plans and responses to the needs of the situation in the absence of pre-packaged solutions (driving during rush hours on Chicago lake shore in winter).


    Reason generic error modeling system l.jpg
    Reason: Generic Error Modeling System decision failure but typically occur when the system breaks down at multiple points along the chain

    Error Types: Slips, Lapses, and Mistakes

    • Slips relate to observable actions associated with attention failures (Skill-Based behavior).

    • Lapses involve memory failures (Skill-Based behavior).

    • Mistakes associated with complex problem solving and relate to a plan that is inadequate to achieve the objective (Rule-Based or Knowledge-Based)

      Error Source: Latent and Active Errors

    • Latent errors are removed from the direct control of the front-line operators and relate to organization level decisions, communication processes, business practices and rules, deficiencies in training etc.

    • Active errors include operator errors at system front end.

      Error Chain: Swiss cheese metaphor.


    Reason generic error modeling system15 l.jpg
    Reason: Generic Error Modeling System decision failure but typically occur when the system breaks down at multiple points along the chain

    Error Chain & Swiss cheese metaphor

    • Numerous factors behind any single decision failure.

    • A single failure analyzed out of context might seem benign.

    • Swiss Cheese metaphor

      • to explain the influence of latent factors on decision failures.

      • need to work backwards to uncover latent factors on decision failures.

      • often a potential error chain is broken by redundancy in the system (feedback mechanisms).

    • Organizational Influences (latent errors)  Unsafe Supervision (latent error)  Preconditions for unsafe acts (latent error)  Unsafe acts (active failures).


    Reason s swiss cheese metaphor l.jpg
    Reason’s “Swiss Cheese” Metaphor decision failure but typically occur when the system breaks down at multiple points along the chain

    Organizational Influences

    Management Hierarchy

    Organization Culture

    Organization Climate

    Organizational Processes

    Institutional Policies

    Institutional Procedures

    Rewards Structure

    Nature of Inter-departmental Cooperation

    Line Management Deficiencies

    Instructional Technology Resources

    Human Resource Constraints

    Budget Constraints

    Business Rules

    Business Practices

    Work Environment

    Front-end System Users

    User’s Knowledge, Experience, Training, & Workload

    Team Work

    Demands of the task

    Latent Factors @ Blunt End

    Active Triggers @ Sharp End


    Reason s swiss cheese metaphor17 l.jpg
    Reason’s “Swiss Cheese” decision failure but typically occur when the system breaks down at multiple points along the chainMetaphor

    Blunt End

    Sharp End

    Latent Conditions

    Organizational Factors

    Latent Conditions

    Latent & Active Conditions

    Line Management Factors

    Supervision

    & Control

    Triggers

    Individual / Team Factors

    Preconditions

    Active Conditions

    Active Conditions

    Gaps or Weakness

    in System Defenses

    System Defenses Working


    Reason s swiss cheese metaphor18 l.jpg
    Reason’s “Swiss Cheese” Metaphor decision failure but typically occur when the system breaks down at multiple points along the chain

    Blunt End

    Sharp End

    Latent Conditions

    Organizational Factors

    Latent Conditions

    Latent & Active Conditions

    Line Management Factors

    Supervision

    & Control

    Triggers

    Individual / Team Factors

    Preconditions

    Active Conditions

    Active Conditions

    Failure in Decision Making

    Trajectory of system failure when Loopholes in the firewall of the system lineup


    Student dropout processes inventory l.jpg
    Student Dropout: Processes Inventory decision failure but typically occur when the system breaks down at multiple points along the chain

    • Recruitment

    • Admissions / Registration

    • Orientation

    • Advising

    • Teaching & Learning Environment


    Recruitment process l.jpg
    Recruitment Process decision failure but typically occur when the system breaks down at multiple points along the chain

    • Identification of Recruits

      • direct mailings, loading test score data, high school and community campus visits, and campus events.

      • graduate students recruitment is decentralized and may involve separate recruiting efforts.

      • international students

    • Managing potential recruits information

    • Assigning and Managing recruiters (includes personal interviews with the prospects)

    • Developing a customized communication plan


    Latent failures recruitment process l.jpg
    Latent Failures: Recruitment Process decision failure but typically occur when the system breaks down at multiple points along the chain

    Non-standardized Protocols

    • Personal interview with the recruits

    • Nature and scope of student communication plan

    • Address needs of special students groups: gender, ethnicity, athletes, economic status etc.

    • GPA computations for prospective graduate student (which degree? undergraduate, graduate, multiple degrees)

      Data / information requirements (in a fragmented system)

    • Availability of test scores and percentiles

    • Data needs of recruiters, admission councilors, departments, special groups on campus.

    • Type and scope of tracking regarding the interventions / special programs


    Latent failures culture recruitment l.jpg
    Latent Failures (Culture): Recruitment decision failure but typically occur when the system breaks down at multiple points along the chain

    Management emphasis is on enrolment relative to retention even thought it is not a sound economic policy.

    A small decrease in student attrition can result in a significant gain in revenue to the institution.

    • A public institution with 2000 freshman enrollment and a dropout rate of 30% can save $1 million for a 10% decrease in the dropout (Levitz, Noel & Richter 1999).

    • 1% increase in the freshman retention will result in a $500,000 gain in additional revenue to the institution (Johnson, 1997)

    • Community college with an enrollment of 15,000 students, and a full-time equivalent student bringing in state funds of $5,000, a 1% decrease in retention increases the tuition revenue by $750,000 (Dr. Jing Luan, Cabrillo College)


    Admission registration process l.jpg
    Admission / Registration Process decision failure but typically occur when the system breaks down at multiple points along the chain

    • Evaluation of prospective student application

      • auto evaluate based on the criteria

      • flag applicants that do not meet the criteria

    • Review by administrators (initial review)

      • administrative officers

      • college / department

        • Look for other factors and background information

    • Review Committees (liberal arts, engineering, etc)

      • Look for additional details

      • Admission based on guidelines

      • Hold for dean’s review

      • Admission decision

    • Number of subjective factors are involved in admission decisions


    Latent failures culture registration l.jpg
    Latent Failures (Culture): Registration decision failure but typically occur when the system breaks down at multiple points along the chain

    Registration procedures to mask some attrition

    • British Open University beginning students register on a temporary basis. If they withdraw within the three months of starting the program, their official registration will not show up on the university records (Guri-Rosenblit, 1999).

      Definition

    • Definition of a dropout varies widely among institutions. The terms retention, attrition, departure, withdrawal are sometimes used interchangeably.

    • Time-to-degree completion or average time to graduation is less accurate due to an increasing number of non-traditional students and the stop-out phenomena.


    Orientation process l.jpg
    Orientation Process decision failure but typically occur when the system breaks down at multiple points along the chain

    Agencies and Scope

    • University level, College level, & Department level

    • Special interest groups / programs

      • Minority Affairs Program

      • Athletics Program

      • Honor’s program

    • Time Duration (1-2 days)

      Processes

    • Faculty: Meet in small groups with faculty.

    • Peers: Interact with peers and other freshmen.

    • Learn about the institution’s academic standard.

    • Support Services: Become familiar with services.

    • Advisor: Meeting to map out academic strategies.

    • Placement: Complete placement testing (if needed ).

    • Pre-Registration: Select fall classes, and register.


    Advising process l.jpg
    Advising Process decision failure but typically occur when the system breaks down at multiple points along the chain

    • Decentralized process and varies from college to college.

    • Categories of academic advisors

      • Academic Professional (AP)

      • Faculty

      • Graduate Student

    • Advising Types

      • New Students

      • Continuing Students

        • Formal advising relationship with a faculty or AP

        • Informal advising relationship

    • Advisor and Student responsibilities

    • Student to advisor ratio

      • UIUC college: between 7 to 60 students per advisor

    • Information system to support Advising


    Latent failures advising l.jpg
    Latent Failures: Advising decision failure but typically occur when the system breaks down at multiple points along the chain

    • 60% of students reported that they are not satisfied with the quality of advising received at their college (National Survey reported in Cuseo 2003; Astin 1993).

    • Insufficient information, getting wrong information relating to instruction, financial aid and billing were some of the negative comments (Survey by Heverly 1999).

    • Need for better Advising Formats & Response Time

      • 24 X 7 Online with 24-hour response

      • Face-to-face regular, evening and weekend hours

    • Student to advisor ratio & quality of student advising

      • UIUC college: between 7 to 60 students per advisor

    • Decentralized / Fragmented Advising System

      • Sharing of student data and advisor notes across campus advising agencies.

    • Degree Audit Reporting System (DARS) not accessible to students.


    Latent failures culture advising l.jpg
    Latent Failures (Culture): Advising decision failure but typically occur when the system breaks down at multiple points along the chain

    • Faculty contracts do not emphasize the importance of advising as a faculty responsibility (Teague & Grites, 1980).

    • Reward structure

      • Often blocks the ability to reward faculty who are genuinely committed to advising” (Creamer & Scott, 2000)

      • Only 12% of postsecondary institutions offered incentives or rewards that recognize outstanding advising of first-year students (Survey: Policy Center on the First Year of College, 2003).

    • Faculty promotion and tenure - advising is typically recognized by giving it only minor consideration (Habley, 1988).

    • Supplementary programs for (at-risk and ethnic) students groups but none for faculty.


    Teaching learning environment l.jpg
    Teaching & Learning Environment decision failure but typically occur when the system breaks down at multiple points along the chain

    Who is teaching the course

    • Research faculty

    • Adjunct faculty

    • Graduate student

      Course delivery format

    • Asynchronous online courses (no instructor contact)

    • Mixed format online courses (with instructor contact)

    • Face-to-face format

      Instructional Design

    • Course structure & role of instructor

    • Assessment and feedback

    • Support for different learning styles

    • Peer interactions & instructor interactions

    • Virtual community support


    Latent failures learning environment l.jpg
    Latent Failures: Learning Environment decision failure but typically occur when the system breaks down at multiple points along the chain

    Institutional commitment to teaching

    • Four-year and junior colleges: teaching emphasis.

    • Universities: research emphasis relative to teaching.

      Instructional Design

    • Rigid course structure with pre-determined course topics.

    • Assessment – multiple choice items graded by TA.

    • Little support for different learning styles

      Nature of instruction

    • Freshman courses with large class size often taught by non-tenured faculty / graduate students.

    • Corresponding course taught without any instructor

    • Online courses with all content online and no scheduled instructor contact.

    • Online courses with scheduled lecture / contact hours taught by untrained professionals.


    Latent failures culture faculty research l.jpg
    Latent Failures (Culture): decision failure but typically occur when the system breaks down at multiple points along the chainFaculty Research

    Rational Choice Model

    • The decision to enroll is a decision to initiate an experiment, a possible outcome of which is dropout. Lowering dropout levels would not necessarily make society better off. (: Manski, 1989).

    • Graduation decision is part of the overall labor market optimizing problem based on an assessment of returns from graduation and the cost of persistence to the student. (DeBrock et al. 1996).

    • Dropout does not necessarily reflect a lack of ability on the part of the student. Dropout cannot be treated as a failure on the part of the educational system.

      Attrition is recognised as a perfectly normal condition within tertiary education. (Tinto1982; Bean 1980)


    Application to student dropout structural layer l.jpg
    Application to Student Dropout: Structural Layer decision failure but typically occur when the system breaks down at multiple points along the chain

    Organizational Influences

    Management Hierarchy

    Regulations: State & Federal

    Organizational Culture: Research Emphasis

    Institutional Priorities: Sports & Entertainment

    Rewards Structure: Emphasis on Research

    Enrollment Management: Focus on Recruitment

    Accountability: Dropout

    Line Management Deficiencies

    Information System: Decentralized and Fragmented

    Human Resource Constraints: Temporary Staff & Graduate TAs

    Budget Constraints: Quality of Advising

    Pedagogy: Converting traditional courses to online format

    Front-end System UsersInstructor Knowledge, Experience, Training, & Workload

    Absence of Team Work & Inter-department Cooperation

    Learning Environment

    Latent Factors @ Blunt End

    Active Triggers @ Sharp End


    Application to student dropout l.jpg
    Application to Student Dropout decision failure but typically occur when the system breaks down at multiple points along the chain

    Blunt End

    Sharp End

    Decentralized / Fragmented Information System

    Vague Procedures

    Latent Conditions

    Insufficient Tutoring Services

    Organizational Factors

    Latent Conditions

    Advisor (Expertise)

    Latent & Active Conditions

    Line Management Factors

    Supervision

    & Control

    Triggers

    Individual / Team Factors

    Preconditions

    Active Conditions

    Non-traditional Student

    Active Conditions

    State & Federal Regulations

    Tenured Faculty with Research Focus

    Institutional Culture: Recruitment Emphasis

    Immature Freshman

    Incomplete Student Plan

    Support Services: Social

    Forced Online Pedagogy (Traditional Course)

    Large Class Size

    Student Dropout

    Trajectory of system failure when Loopholes in the firewall of the system lineup


    Application to student dropout process layer l.jpg
    Application to Student Dropout: Process Layer decision failure but typically occur when the system breaks down at multiple points along the chain

    Triggers

    Incomplete information about the Prospect

    Incomplete Communication Plan

    Staff/Recruiter Workload

    Institutional factors

    Recruitment

    Over-whelmed with Advising Information

    Admission

    Decentralized / fragmented Information System

    Orientation

    Immature Freshman

    Over-worked Athlete

    Advising

    Asynchronous Online Course

    Learning Environment

    Decentralized Information System

    Vague Recruitment Guidelines

    Instructor Experience (TA)

    Federal & State Regulations

    Placement Credits

    Transfer Credits

    Support Services

    Freshman Course (large class size)

    Student

    Dropout

    Trajectory of system failure

    when Loopholes in the firewall of the system lineup

    System Defenses working


    Application to student dropout process layer35 l.jpg
    Application to Student Dropout: Process Layer decision failure but typically occur when the system breaks down at multiple points along the chain

    Triggers

    Incomplete information about the Prospect

    Incomplete Communication Plan

    Staff/Recruiter Workload

    Institutional factors

    Recruitment

    Over-whelmed with Advising Information

    Admission

    Decentralized / fragmented Information System

    Orientation

    Immature Freshman

    Over-worked Athlete

    Advising

    Learning Environment w/:

    Instructor as Coach

    Small class-size

    Team-based Peer Learning

    Relevant Projects

    Instructor Interactions

    Assessment & Feedback

    Decentralized Information System

    Vague Recruitment Guidelines

    Placement Credits

    Transfer Credits

    Support Services

    Student

    Completes Course

    System Defenses working when Loopholes in the firewall of the system gets deflected


    Interventions national level l.jpg
    Interventions: National Level decision failure but typically occur when the system breaks down at multiple points along the chain

    Federal & State Initiatives

    • National priority (mission is to educate).

    • Address accountability and legal liability issues.

    • Appropriations and student performance.

    • Student Attrition Management System (Shaik, 2003a).

    • Culture of Retention (Shaik, 2003b).

      Student Attrition Management System

    • Based on standardized metrics and failures typology.

    • Centralized national database on student attrition.

    • Online web-based system with a user friendly interface.

    • Reporting (voluntary and mandatory) of dropout incidents at (institutional) process level.

    • Recovery management framework.


    Interventions organization level l.jpg
    Interventions: Organization Level decision failure but typically occur when the system breaks down at multiple points along the chain

    Assessment of work environment

    • Methodologies:

      • Cognitive Task Analysis (What is);

      • Cognitive Work Analysis (What should be);

      • Fault-tree Methodology;

    • Goal: identify latent errors & redesign environment.

      Reward structure

    • Goal: to encourage retention by faculty and staff.

      Research

    • Validated and replicable using time-series and cross-program data from the national database.

    • Reports on dropout to go beyond data collection.

    • Pattern Analysis to identify the causes and to discover robust patterns which can then be used as forecasts from operational and reporting data.


    Selected references l.jpg
    Selected References decision failure but typically occur when the system breaks down at multiple points along the chain

    • Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education, 12, 155-187.

    • Boshier, R. (1973). Educational participation and dropout: A theoretical model. Adult Education, 23, 255–282.

    • Cabrera, A. F., Nora, A., and Castaneda, M. B. (1993). College persistence: Structural equations modeling test of an integrated model of student retention. Journal of Higher Education, 64(2), 123-139.

    • Cross, K. P. (1981). Adults as learners. San Francisco: Jossey-Bass.

    • Draper, S. (2003). Tinto’s model of student retention. URL: http://www.psy.gla.ac.uk/~steve/localed/tinto.html

    • Fishbein, M. and Ajzen, I (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.

    • Rasmussen, J. (1983). Skills, Rules and Knowledge; Signals, Signs and Symbols and Other Distinctions in Human Performance Models. IEEE Transactions on System, Man and Cybernetics. SMC-13 (3). 257-266.

    • Norman, D. (2002). The Design of Everyday Things. Basic Books.

    • Reason J. (1990). Human Error. Cambridge University Press.

    • Shaik, N. (2003a). Student Attrition Management System: An Organization with Memory – A Conceptual Framework . Working paper, Division of Academic Outreach, University of Illinois.

    • Shaik, N. (2003b). Culture of Student Retention: Alternative Framework. Working paper, Division of Academic Outreach, University of Illinois.


    Selected references39 l.jpg
    Selected References decision failure but typically occur when the system breaks down at multiple points along the chain

    • Spady, W. G., (1971) Drop-outs from Higher Education: An Interdisciplinary Review & Synthesis, Interchange, 64-85.

    • Seidman, A. (1996). Retention Revisited: RET = E Id + (E + I + C)Iv. College and University, 71(4), 18-20.

    • Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Student Attrition, Chicago: University of Chicago Press.

    • Vicente, K. and Rasmussen, J. (1992). Ecological Interface Design: Theoretical Foundations. IEEE Transactions on Systems, Man, and Cybernetics, 22(4), 589-606.

    • Virginia Commonwealth University (2000) Retention 2000 Recommendations. http://www.students.vcu.edu/dsa/retention2000/advising

    • Witte J. W., Forbes, S. E. & Witte, M. M (2000). Identity Theory and Persistence: A Tentative Synthesis of Tinto, Erikson, and Houle. Journal of Integrative Psyhcology. Vol 2.


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