A System Dynamics-Based Interactive Learning Environment for Online Formative (Self-)Assessment of Wanna-Be Entrepreneurs’ Performance Management Capabilities
Abstract
:1. Introduction
1.1. Entrepreneurial Skills, Competencies and Capabilities
1.2. Performance Management as a Key Managerial Skill for Entrepreneurs
1.3. The Influence of Self-Perceptions and Beliefs on Entrepreneurial Entry Decisions
2. The Role System Dynamics-Based Interactive Learning Environments in Fostering Formative Assessment
2.1. System Dynamics-Based Interactive Learning Environment, Constructivism and Learning
2.2. Formative Assessment and Learning
Formative Self-Assessment
2.3. System Dynamics-Based Interactive Learning Environment as a Tool for Formative Assessment
3. Method
3.1. The Theoretical Foundation of the ILE
3.2. The Stucture of the ILE
3.2.1. The ILE Interface
- Performance: current and expected (desired) performance;
- Performance moderators: employee goal commitment; employee competence; employee well-being and employee self-efficacy;
- Performance Mediators: personal goals; expectancy of goal attainment and performance beyond expectation effect;
- Income statement: revenues; costs and profit.
- Rapidly capturing ideas about the reasons behind dynamic behaviors.
- Gathering and documenting the cognitive models of individuals or teams.
- Conveying the important feedback loops that are thought to contribute to a problem.
3.2.2. The CLD of the ILE
3.2.3. The ILE Dashboard
3.2.4. The ILE Features to Support the Online Formative Assessment Procedures
3.3. “Black Box” versus “Glass Box”: Which Is More Beneficial for a System Dynamics-Based ILE?
4. Results
4.1. Promoting Formative (Self-)Assessment through the ILE
4.2. Two Cases of Formative (Self-)Assessment
4.2.1. First Simulation Session
Run #1
Run #2
Run #3
Run #4
4.2.2. Second Simulation Session
Run #1
Run #2
5. Discussion
5.1. The Transferability of the Adopted Methodology: Some Examples of ILE Applied to Different Contexts and Target Groups
5.2. The Role Played by the Teacher and Learner in the Use of Interactive Learning Environments and the Benefits Generated for Them
6. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A. Full Model Equations
Variable Name | Equation | Properties | Units |
Stock variables | |||
Costs(t) | Costs(t − dt) + (Costs_Inflow) × dt | INIT Costs = 0 | EUR |
Employees_Competence(t) | Employees_Competence(t − dt) + (Net_Change_in_Employees_Competence) × dt | INIT Employees_Competence = 0.7 | Dimensionless |
Employees_Goal_Commitment(t) | Employees_Goal_Commitment(t − dt) + (Net_Change_in_Employee_Goal_Commitment) × dt | INIT Employees_Goal_Commitment = 0.7 | Dimensionless |
“Employees_Self-Efficacy”(t) | “Employees_Self-Efficacy”(t − dt) + (“Net_Change_in_Employees_Self-Efficacy”) × dt | INIT “Employees_Self-Efficacy” = 0.7 | Dimensionless |
“Employees_Well-Being”(t) | “Employees_Well-Being”(t − dt) + (“Net_Change_in_Employee_Well-Being”) × dt | INIT “Employees_Well-Being” = 0.7 | Dimensionless |
Performance(t) | Performance(t − dt) + (Net_Change_in_Performance) × dt | INIT Performance = 0.5 | Dimensionless |
Revenue(t) | Revenue(t − dt) + (Revenue_Inflow) × dt | INIT Revenue = 0 | EUR |
Flow variables | |||
Costs_Inflow | (Revenue_Inflow × 0.85) + (Overall_effort_for_HR_practices × Cost_for_HR_practice)/Time_to_Costs | EUR/Months | |
Net_Change_in_Employee_Goal_Commitment | MIN(1 − Employees_Goal_Commitment; Reward_System + Involvement) /EGC_Adjustment_Time | Dimensionless/Months | |
“Net_Change_in_Employee_Well-Being” | MIN(1 − “Employees_Well-Being”; “Well-being”)/WB_Adjustment_Time | Dimensionless/Months | |
Net_Change_in_Employees_Competence | MIN(1− Employees_Competence; (Training + Recruitment_and_Selection))/EC_Adjustment_Time | Dimensionless/Months | |
“Net_Change_in_Employees_Self-Efficacy” | MIN(1 − “Employees_Self-Efficacy”; (“Employees_Self-Efficacy” × Expectancy_of_Goal_Attainment × “EGA_on_S-E_Effect”)-“Employees_Self-Efficacy”)/”E_S-E_Adjustment_Time” | Dimensionless/Months | |
Net_Change_in_Performance | ((Personal_Goal × Performance_Beyond_Expectation_Effect) − Performance)/Performance_Adjustment_Time | Dimensionless/Months | |
Revenue_Inflow | (Performance × Revenue_for_Performance)/Time_to_Revenue | Euros/Months | |
Auxiliary and input variables | |||
Activate_1_YR_PAUSE | 0 | Dimensionless | |
Activate_I[Low] | −0.2 × “Activate_I-Low” | Dimensionless | |
Activate_I[Medium] | 0.05 × “Activate_I-Medium” | ||
Activate_I[High] | 0.2 × “Activate_I-High” | ||
“Activate_I-High” | 0 | Dimensionless | |
“Activate_I-Low” | 0 | Dimensionless | |
“Activate_I-Medium” | 0 | Dimensionless | |
Activate_R&S[Low] | −0.1 × “Activate_R&S-Low” | Dimensionless | |
Activate_R&S[Medium] | 0.05 × “Activate_R&S-Medium” | ||
Activate_R&S[High] | 0.1 × “Activate_R&S-High” | ||
“Activate_R&S-High” | 0 | Dimensionless | |
“Activate_R&S-Low” | 0 | Dimensionless | |
“Activate_R&S-Medium” | 0 | Dimensionless | |
Activate_RS[Low] | −0.2 × “Activate_RS-Low” | Dimensionless | |
Activate_RS[Medium] | 0.05 × “Activate_RS-Medium” | ||
Activate_RS[High] | 0.2 × “Activate_RS-High” | ||
“Activate_RS-High” | 0 | Dimensionless | |
“Activate_RS-Low” | 0 | Dimensionless | |
“Activate_RS-Medium” | 0 | Dimensionless | |
“Activate_T-High” | 0 | Dimensionless | |
“Activate_T-Low” | 0 | Dimensionless | |
“Activate_T-Medium” | 0 | Dimensionless | |
Activate_Training[Low] | 0 × “Activate_T-Low” | Dimensionless | |
Activate_Training[Medium] | 0.1 × “Activate_T-Medium” | ||
Activate_Training[High] | 0.2 × “Activate_T-High” | ||
Activate_WB[Low] | −0.2 × “Activate_WB-Low” | Dimensionless | |
Activate_WB[Medium] | 0.05 × “Activate_WB-Medium” | ||
Activate_WB[High] | 0.2 × “Activate_WB-High” | ||
“Activate_WB-High” | 0 | Dimensionless | |
“Activate_WB-Low” | 0 | Dimensionless | |
“Activate_WB-Medium” | 0 | Dimensionless | |
Assigned_Goal | 0.5 | Dimensionless | |
Cost_for_HR_practice | 2,500,000 | EUR/Dimensionless | |
“E_S-E_Adjustment_Time” | 1 | Months | |
EC_Adjustment_Time | 1 | Months | |
“EGA_on_S-E_Effect” | IF Expectancy_of_Goal_Attainment = 1 THEN (“Employees_Self-Efficacy” + (1 − “Employees_Self-Efficacy”)) × 1.02 ELSE 1 | Dimensionless | |
EGC_Adjustment_Time | 1 | Months | |
Expectancy_of_Goal_Attainment | GRAPH(MIN(1; (Employees_Competence/Assigned_Goal))) Points: (0.5000, 0.98), (0.5500, 0.982), (0.6000, 0.984), (0.6500, 0.986), (0.7000, 0,988), (0.7500, 0.99), (0.8000, 0.992), (0.8500, 0.994), (0.9000, 0.996), (0.9500, 0.998), (1.0000, 1) | Dimensionless | |
Goal_Difficulty_and_Specificity | GRAPH(Assigned_Goal/Performance) Points: (0.000, 1.000), (0.125, 1.000), (0.250, 1.000), (0.375, 1.000), (0.500, 1.000), (0.625, 1.000), (0.750, 1.000), (0.875, 1.000), (1.000, 1.000), (1.125, 1.077), (1.250, 1.189), (1.375, 1.000), (1.500, 0.900), (1.625, 0.776630599122), (1.750, 0.733049523696), (1.875, 0.702415575137), (2.000, 0.679) | Dimensionless | |
Gross_Profit | Revenue-Costs | REPORT IN TABLE AS STOCK | EUR |
Involvement | MIN((1 − Employees_Goal_Commitment); SUM(Activate_I)) | Dimensionless | |
Online_Form_is_active | 0 | Dimensionless | |
Overall_effort_for_HR_practices | “Well-being” + Involvement + Training + Reward_System + Recruitment_and_Selection | Dimensionless | |
Performance_Adjustment_Time | 3 | Months | |
Performance_Beyond_Expectation_Effect | GRAPH(IF Employees_Competence > Assigned_Goal AND Assigned_Goal >= 0.6 THEN Performance × 2 ELSE 0) Points: (0.7000, 1), (0.7300, 1.005), (0.7600, 1.01), (0.7900, 1.015), (0.8200, 1.02), (0.8500, 1.025), (0.8800, 1.03), (0.9100, 1.035), (0.9400, 1.04), (0.9700, 1.045), (1.0000, 1.05) | Dimensionless | |
Personal_Goal | MIN(MIN(MIN(MIN((Assigned_Goal × Goal_Difficulty_and_Specificity); Employees_Competence); Employees_Goal_Commitment); “Employees_Well-Being”); “Employees_Self-Efficacy”) | REPORT IN TABLE AS STOCK | Dimensionless |
Recruitment_and_Selection | MIN((1 − Employees_Competence); SUM(Activate_R&S)) | Dimensionless | |
Revenue_for_Performance | 4,500,000 | EUR/Dimensionless | |
Reward_System | MIN((1 − Employees_Goal_Commitment); SUM(Activate_RS)) | Dimensionless | |
Sim_Duration | 2 | Seconds | |
TIME_GAME | TIME × Activate_1_YR_PAUSE | Months | |
Time_to_Costs | 1 | Months | |
Time_to_Revenue | 1 | Months | |
Training | MIN((1 − Employees_Competence); SUM(Activate_Training )) | Dimensionless | |
WB_Adjustment_Time | 1 | Months | |
“Well-being” | MIN((1 − “Employees_Well-Being”); SUM(Activate_WB)) | Dimensionless |
Run Specs | |
Start Time | 0 |
Stop Time | 36 |
DT | 1/1 |
Fractional DT | True |
Save Interval | 1 |
Sim Duration | 36 |
Time Units | Months |
Pause Interval | 0 |
Integration Method | Euler |
Keep all variable results | True |
Interaction Mode | Flight Simulation |
Run By | Run by Module |
Calculate loop dominance information | False |
References
- Aas, Tor Helge, and Ahmad Alaassar. 2018. The impact of visual performance management on decision-making in the entrepreneurial process. International Journal of Innovation Management 22: 1840002. [Google Scholar] [CrossRef]
- Bass, Bernard M. 1985. Leadership and Performance Beyond Expectations. Glencoe: Free Press. [Google Scholar]
- Bauman, Antonina, and Carol Lucy. 2019. Enhancing entrepreneurial education: Developing competencies for success. The International Journal of Management Education 19: 100293. [Google Scholar] [CrossRef]
- Bianchi, Carmine, and Enzo Bivona. 2000. Commercial and financial policies in family firms: The small business growth management flight simulator. Simulation & Gaming 31: 197–229. [Google Scholar]
- Black, Paul, and Dylan Wiliam. 2006. Assessment for learning in the classroom. In Assessment and Learning. Edited by John Gardner. London: Sage Publications. [Google Scholar]
- Burger-Helmchen, Thierry. 2008. Plural-entrepreneurial activity for a single start-up: A case study. The Journal of High Technology Management Research 19: 94–102. [Google Scholar] [CrossRef]
- Ceresia, Francesco. 2018. The Role of Entrepreneurship Education in Fostering Entrepreneurial Intentions and Performances: A Review of 30 Years of Research. Equidad y Desarrollo 31: 47–66. [Google Scholar] [CrossRef]
- Ceresia, Francesco, and Claudio Mendola. 2019. Entrepreneurial self-identity, perceived corruption, exogenous and endogenous obstacles as antecedents of entrepreneurial intention in Italy. Social Sciences 8: 54. [Google Scholar] [CrossRef]
- Ceresia, Francesco, and Claudio Mendola. 2020. Am I an entrepreneur? Entrepreneurial self-identity as an antecedent of entrepreneurial intention. Administrative Sciences 10: 46. [Google Scholar] [CrossRef]
- Davidsen, Pål I. 1996. Educational features of the system dynamics approach to modelling and simulation. Journal of Structured Learning 12: 269–90. [Google Scholar]
- Driscoll, Marcy. 2000. Psychology of Learning for Instruction. Boston: Allyn and Bacon. [Google Scholar]
- Ellis, Cath. 2013. Broadening the scope and increasing usefulness of learning analytics: The Case for assessment analytics. British Journal of Educational Technology 44: 662–64. [Google Scholar] [CrossRef]
- Fauchart, Emmanuelle, and Marc Gruber. 2011. Darwinians, communitarians, and missionaries: The role of founder identity in entrepreneurship. The Academy of Management Journal 54: 935–57. [Google Scholar] [CrossRef]
- Gatewood, Elizabeth J., Kelly G. Shaver, and William B. Gartner. 1995. A longitudinal study of cognitive factors influencing startup behaviors and success at venture creation. Journal of Business Venturing 10: 371–91. [Google Scholar] [CrossRef]
- Gibb, Allan A. 1987. Education for enterprise: Training for small-business initiation—Some contrasts. Journal of Small Business & Entrepreneurship 4: 42–47. [Google Scholar]
- Hahn, Davide, Tommaso Minola, Anita Van Gils, and Jolien Huybrechts. 2017. Entrepreneurial education and learning at universities: Exploring multilevel contingencies. Entrepreneurship & Regional Development 29: 945–74. [Google Scholar]
- Hattie, John. 2012. Visible Learning for Teachers: Maximizing Impact on Learnings. New York: Routledge. [Google Scholar]
- Kokina, Julia, Dessislava Pachamanova, and Andrew Corbett. 2017. The role of data visualization and analytics in performance management: Guiding entrepreneurial growth decisions. Journal of Accounting Education 38: 50–62. [Google Scholar] [CrossRef]
- Kuratko, Donald F., and Michael H. Morris. 2018. Examining the future trajectory of entrepreneurship. Journal of Small Business Management 56: 11–23. [Google Scholar] [CrossRef]
- Latham, Gary P., and Edwin A. Locke. 1991. Self-regulation through goal setting. Organizational Behavior and Human Decision Processes 50: 212–47. [Google Scholar] [CrossRef]
- Latham, Gary P., and Edwin A. Locke. 2007. New developments in and directions for goal-setting research. European Psychologist 12: 290–300. [Google Scholar] [CrossRef]
- Lichtenstein, Gregg A., and Thomas S. Lyons. 2001. The entrepreneurial development system: Transforming business talent and community economies. Economic Development Quarterly 15: 3–20. [Google Scholar] [CrossRef]
- Locke, Edwin A., and Gary P. Latham. 1990. Work motivation and satisfaction: Light at the end of the tunnel. Psychological Science 1: 240–46. [Google Scholar] [CrossRef]
- Locke, Edwin A., and Gary P. Latham. 2002. Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist 57: 705. [Google Scholar] [CrossRef]
- Locke, Edwin A., and Gary P. Latham. 2004. What should we do about motivation theory? Six recommendations for the twenty-first century. Academy of Management Review 29: 388–403. [Google Scholar]
- Mayanja, Samuel, Michael Omeke, Josue Vajeru Tibamwenda, Henry Mutebi, and Fredrick Mufta. 2021. The mediating role of the novelty ecosystem between personality traits, entrepreneurial networks and entrepreneurial ambidexterity among small and medium enterprises. Journal of Global Entrepreneurship Research 11: 17. [Google Scholar] [CrossRef]
- Nabi, Ghulam, Francisco Liñán, Alain Fayolle, Norris Krueger, and Andreas Walmsley. 2017. The impact of entrepreneurship education in higher education: A systematic review and research agenda. Academy of Management Learning and Education 16: 277–99. [Google Scholar] [CrossRef]
- Pennetta, Selene, Francesco Anglani, and Shane Mathews. 2023. Navigating through entrepreneurial skills, competencies and capabilities: A systematic literature review and the development of the entrepreneurial ability model. Journal of Entrepreneurship in Emerging Economies, ahead-of-print. [Google Scholar] [CrossRef]
- Pfeffer, Jeffrey, and Robert I. Sutton. 2000. The Knowing–Doing Gap. Boston: Harvard Business School Press. [Google Scholar]
- Phillips, Denis C. 1995. The good, the bad, and the ugly: The many faces of constructivism. Educational Researcher 24: 5–12. [Google Scholar] [CrossRef]
- Prufer, Jens, and Patricia Prufer. 2020. Data science for entrepreneurship research: Studying demand dynamics for entrepreneurial skills in the Netherlands. Small Business Economics 55: 651–72. [Google Scholar] [CrossRef]
- Sadler, Philip M., and Eddie Good. 2006. The Impact of self- and peer-grading on student learning. Educational Assessment 11: 1–31. [Google Scholar] [CrossRef]
- Sakhdari, Kamal, Henri Burgers, Jahangir Yadollahi Farsi, and Sasan Rostamnezhad. 2020. Shaping the organisational context for corporate entrepreneurship and performance in Iran: The interplay between social context and performance management. The International Journal of Human Resource Management 31: 1020–46. [Google Scholar] [CrossRef]
- Shaw, Kathryn, and Anders Sørensen. 2019. The productivity advantage of serial entrepreneurs. ILR Review 72: 1225–61. [Google Scholar] [CrossRef]
- Shepherd, Dean A., Williams A. Trenton, and Holger Patzelt. 2015. Thinking about entrepreneurial decision making: Review and research agenda. Journal of management 41: 11–46. [Google Scholar] [CrossRef]
- Solórzano-García, Marta, Navio-Marco Julio, and Ana Laguia. 2022. The influence of intrinsic motivation and contextual factors on MOOC students’ social entrepreneurial intentions. Interactive Learning Environments 30: 1768–80. [Google Scholar] [CrossRef]
- Spector, J. Michael, and Pål I. Davidsen. 1997. Creating engaging courseware using system dynamics. Computers in Human Behavior 13: 127–55. [Google Scholar] [CrossRef]
- Spector, J. Michael, Dean L. Christensen, Alexei V. Sioutine, and Dalton McCormack. 2001. Models and simulations for learning in complex domains: Using causal loop diagrams for assessment and evaluation. Computers in Human Behavior 17: 517–45. [Google Scholar] [CrossRef]
- Spector, J. Michael, Dirk Ifenthaler, Demetrios Sampson, Lan (Joy) Yang, Evode Mukama, Amali Warusavitarana, Kulari Lokuge Dona, Koos Eichhorn, Andrew Fluck, Ronghuai Huang, and et al. 2016. Technology enhanced formative assessment for 21st century learning. Educational Technology & Society 19: 58–71. [Google Scholar]
- Spector, Jonathan Michael. 2014. Conceptualizing the emerging field of smart learning environments. Smart Learning Environments 1: 2. [Google Scholar] [CrossRef]
- Spector, Jonathan Michael. 2015. Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives, 2nd ed. New York: Routledge. [Google Scholar]
- Sterman, John. 2000. Business Dynamics. Martinsville: Irwin/McGraw-Hill. [Google Scholar]
- Sterman, John. 2014. Interactive web-based simulations for strategy and sustainability: The MIT Sloan LearningEdge management flight simulators, Part I. System Dynamics Review 30: 89–121. [Google Scholar] [CrossRef]
- Thomke, Stefan H. 2003. Experimentation Matters: Unlocking the Potential of New Technologies for Innovation. Harvard: Harvard Business Press. [Google Scholar]
- van Dijkum, Cor, and Hans Landsheer. 2000. Experimenting with a nonlinear dynamic model of juvenile criminal behavior. Simulation & Gaming 31: 479–90. [Google Scholar]
- Yeganegi, Sepideh, Andre O. Laplume, Parshotam Dass, and Nathan S. Greidanus. 2019. Individual-level ambidexterity and entrepreneurial entry. Journal of Small Business Management 57: 1444–63. [Google Scholar] [CrossRef]
- Yen, Wan-Chu, and Hsin-Hui Lin. 2022. Investigating the effect of flow experience on learning performance and entrepreneurial self-efficacy in a business simulation systems context. Interactive Learning Environments 30: 1593–1608. [Google Scholar] [CrossRef]
- Zahra, Shaker A., and Dennis M. Garvis. 2000. International corporate entrepreneurship and firm performance: The moderating effect of international environmental hostility. Journal of Business Venturing 15: 469–92. [Google Scholar] [CrossRef]
- Zahra, Shaker A., Harry J. Sapienza, and Per Davidsson. 2006. Entrepreneurship and dynamic capabilities: A review, model and research agenda. Journal of Management Studies 43: 917–55. [Google Scholar] [CrossRef]
Michele lives in Paris and is 70 years old. For the past 50 years, he has worked as the CEO of the family business. The company was founded by his grandfather, Louis, in 1910 in a small warehouse on the outskirts of Paris. The company specializes in the production and wholesale of designer furniture. Under Michele’s leadership, the company has experienced significant growth and has become a solid presence in the industry. As of 2022, the company had 900 employees and closed its balance sheet with a turnover of €81 million and a gross profit of just over €12 million. However, in the last 3 years, Michele has been feeling tired and, despite his reluctance, has decided to retire. Since he has no children or other interested relatives to take over the management of the company, he must choose between selling the company or appointing an external CEO. After much contemplation, Michele decides to appoint an administrator. His wife, Joanna, is in agreement with this decision. He knows that his husband would not tolerate the idea of seeing the company he has dedicated his entire professional life to close. Michele chooses to appoint engineer Joseph Dreyfuss as the new CEO. Joseph has been Michele’s right-hand man for the past 15 years, and Michele has a great deal of trust in him. Since he does not intend to influence Joseph’s managerial decisions, Michele tasks the new CEO with building his own team of executives in the field of human resources, which Michele has always considered to be strategic for achieving performance objectives. In 2018, the company acquired a simulation model, a business intelligence tool that allows for the estimation of future turnover based on decisions made by the company’s management, with a particular focus on goal-oriented and strategic human resources development processes. Engineer Dreyfuss is honored that Michèle chose him and feels a great sense of responsibility in leading the company towards a new phase of development. He recognizes the need to steer the company without Michèle’s influence and decides to prioritize the development of an intervention plan in the field of human resources to improve company performance. He firmly believes that focusing on human resources is crucial in achieving corporate objectives. To implement his plan, engineer Dreyfuss appoints three new managers to head three specific areas within the human resources department:
|
Some teams will be formed, each made up of four people. Each team’s objective is to:
|
The four members of each team will elect the CEO. The CEO will appoint the following managers from among the remaining three people:
The talent manager is tasked with planning talent acquisition strategies, developing internal promotion policies, and negotiating contracts and is also responsible for managing the following human resource practices: training, recruitment, and selection. The motivational manager oversees employees, helping them learn new skills, perform job tasks, and achieve shared goals and is responsible for the following human resource practices: employee involvement and reward system. The well-being manager is in charge of defining workplace well-being strategies and programs within the organization and is responsible for the following human resource practice: employee well-being. |
RUN | Initial Condition | Change in | Results | Graphs | |||||
---|---|---|---|---|---|---|---|---|---|
AG | WB | T | I | RS | R&S | ||||
1 | P = 0.50; AG = 0.60 | P = 0.63; GP = 15.12 M | See Figure 4 | ||||||
2 | P = 0.50; AG = 0.80 | P = 0.59; GP = 15.37 M | |||||||
3 | P = 0.50; AG = 1.00 | P = 0.59; GP = 13.93 M | |||||||
4 | P = 0.50; AG = 0.60 | 0.8 T = 6°mo | M T = 16°mo | H T = 10°mo | M T = 10°mo | P = 0.79; GP = 16.73 M |
RUN | Initial Condition | Change in | Results | Graphs | |||||
---|---|---|---|---|---|---|---|---|---|
AG | WB | T | I | RS | R&S | ||||
1 | P = 0.30; AG = 0.90 | P = 0.52; GP = 14.00 M | See Figure 5 | ||||||
2 | P = 0.30; AG = 0.90 | H T = 16°mo | H T = 12°mo | M T = 24°mo | M T = 12°mo | P = 0.79; GP = 14.91 M | |||
3 | P = 0.30; AG = 0.70 | 0.9 T = 12°mo | H T = 16°mo | H T = 18°mo | M T = 24°mo | M T = 18°mo | M T = 18°mo | P = 0.73; GP = 14.58 M | |
4 | P = 0.30; AG = 1.00 | 0.9 T = 12°mo | H T = 16°mo | H T = 12°mo | H T = 16°mo | H T = 12°mo | H T = 16°mo | P = 0.93; GP = 14.59 M |
ILE Title | Salt Seller | Eclipsing the Competition | Platform Wars | Fishbanks | CleanStart | World Climate |
---|---|---|---|---|---|---|
Strategic issues addressed | Pricing dynamics in imperfectly competitive markets | Strategy in the presence of learning curves and scale economies | Strategy in multisided platform markets; direct and indirect network externalities | Strategy for open access renewable resources | Entrepreneurship; marketing, product development, financing, employee ownership | Climate policy; negotiations; collective action |
Scientific domains | Economics, strategy, decision making | Economics, strategy, technology and innovation, energy management, environmental management, sustainability | Economics, strategy, technology and innovation, system dynamics | Economics, strategy, negotiations, sustainability, environmental management, public policy, resource economics | Entrepreneurship, human resources, economics, strategy, sustainability | Economics, strategy, negotiations, sustainability, environmental management, public policy, resource economics |
Trainer | Learner | ||
---|---|---|---|
Facilitator | The role of a facilitator is crucial in the learning process. They act as a guide who introduces new information and concepts to learners, presenting it in a clear and organized manner. They break down complex topics into simpler parts and provide explanations and examples to help learners grasp the content. Facilitators also guide learners through different learning activities and exercises, ensuring they understand and apply what they have learned. They create a supportive and interactive learning environment where learners feel comfortable asking questions and seeking further clarification. | Self-Directed Learner | The individual sets learning objectives based on their career goals and job requirements, then creates a learning plan to achieve those objectives. They research and select courses, webinars, or books that align with their learning plan, and actively engage in the learning experience to acquire new knowledge and skills. |
Assessor | The role of an assessor is to evaluate learners’ progress and provide feedback on their performance. Assessors design and administer various forms of assessments, such as quizzes, assignments, projects, or exams, to gauge learners’ understanding and mastery of the subject matter. They provide constructive feedback to learners, highlighting areas of strength and areas that need improvement. Assessors also assign grades or scores to learners’ work, objectively measuring their competence. This role helps learners understand their strengths and weaknesses, encouraging them to focus on areas that require further development. | Participant and Collaborator | The individual participates in training sessions and interactive learning activities, asking thoughtful questions and actively contributing to discussions. They apply what they have learned to real-world scenarios, seeking out feedback and coaching to improve their performance. The individual works with their peers to solve problems and complete projects, sharing their expertise and supporting others’ learning. They actively listen to feedback and apply it to improve their understanding of the subject matter. |
Collaborator | The role of a collaborator is to foster a culture of collaboration and peer-to-peer interaction in the learning environment. Collaborators encourage learners to work together in groups, engaging in discussions, sharing ideas, and solving problems collectively. They create opportunities for learners to collaborate on projects, assignments, or group activities, promoting teamwork and the exchange of diverse perspectives. Collaborators facilitate effective communication and cooperation among learners, creating a supportive social environment that enhances the learning experience. | Referee and Self-Assessor | The individual provides constructive feedback to their peers, helping them to identify areas for improvement and offering suggestions for future learning opportunities. The individual regularly assesses their progress, identifying areas where they need to improve and setting new learning objectives. They seek out feedback from their peers and reflect on their own performance to adjust their learning strategy. |
Advisor | The role of an advisor is to provide personalized guidance and support to learners. Advisors take into account learners’ unique needs, interests, and goals, tailoring the learning experience to meet their specific requirements. They offer individualized advice on course selection, career planning, or further educational opportunities. Advisors also provide mentorship and counseling, helping learners overcome challenges, set realistic goals, and make informed decisions. By offering personalized guidance, advisors assist learners in maximizing their potential and achieving their desired outcomes. | Performer and Leader | The individual applies the knowledge and skills acquired during training to perform their job duties with proficiency and confidence, seeking out additional learning opportunities to stay up-to-date on best practices and trends. The individual shares their expertise with others, mentoring and coaching team members to improve their performance. They advocate for continuous learning and professional development within their organization, encouraging their peers to adopt these learning styles as well. |
Trainer | Learner | ||
---|---|---|---|
Enhanced Student Engagement | Interactive learning environments actively involve learners, promoting better educational outcomes and improved student engagement, which, in turn, ensures that learners have a better learning experience. | Personalized Learning | Interactive learning environments can adapt to suit learners’ individual learning styles, making the learning experience more personalized and effective |
Real-time Assessment | Interactive learning environments provide instant feedback to learners, which helps instructors to identify areas that require attention and adjust their teaching strategies accordingly. | Interactive Learning Experience | Interactive learning environments offer learners the opportunity to engage actively in the learning process, facilitating better retention of knowledge. |
Increased Efficiency | Interactive learning environments enable instructors to manage larger class sizes, delivering content more efficiently and cost-effectively. | Real-time Feedback | Interactive learning environments provide learners with instant feedback, which helps them to identify gaps in their knowledge and improve immediately. |
Improved teaching skills | Interactive learning environments allow instructors to refine and practice their teaching skills, with vicariously gained role-playing experiences. | Collaborative Learning | Interactive learning environments encourage learners to work collaboratively, which has proven benefits for memory retention and enhanced peer learning. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ceresia, F. A System Dynamics-Based Interactive Learning Environment for Online Formative (Self-)Assessment of Wanna-Be Entrepreneurs’ Performance Management Capabilities. Adm. Sci. 2024, 14, 3. https://doi.org/10.3390/admsci14010003
Ceresia F. A System Dynamics-Based Interactive Learning Environment for Online Formative (Self-)Assessment of Wanna-Be Entrepreneurs’ Performance Management Capabilities. Administrative Sciences. 2024; 14(1):3. https://doi.org/10.3390/admsci14010003
Chicago/Turabian StyleCeresia, Francesco. 2024. "A System Dynamics-Based Interactive Learning Environment for Online Formative (Self-)Assessment of Wanna-Be Entrepreneurs’ Performance Management Capabilities" Administrative Sciences 14, no. 1: 3. https://doi.org/10.3390/admsci14010003