Collection

2011 Pacific Southwest Section Meeting

Authors

Bruno Osorno; William Oh

solar cellsFig. 2 is the equivalent circuit of a simplified single-diode model (SSDM) of PV cells. Thecurrent through a PV cell is given by;   v  iRs   i  i ph  isat e t   1 v (1)     AkT vt T   (2) q Proceedings of the 2011 PSW

Collection

2010 Northeast Section Meeting

Authors

Stephanie Parker; J. Kemi Ladeji-Osias

FPGA.AcknowledgementThis work was supported by the Chesapeake Information Based Aeronautics Consortium (CIBAC) atMorgan State University.Reference1 S.D. Young, S. Kakarlapudi, and M. Uijt de Young, “A Shadow Detection and Extraction Algorithm Using Digital Elevation models and X-bandWeather Radar Measurements”, Int. J. Remote Sensing, 26(8): 1531-1549, 2005.2 Sonka Milan, Image Processing Analysis, and Machine Vision, 1999, California: Brooks/Cole Publishing Company3 Field Programmable Gate Array, http://en.wikipedia.org/wiki/FPGA (Accessed 7/22/2009)4 What is VHDL?http://74.125.47.132/search?q=cache:MlxxUJ50YEJ:www.doulos.com/knowhow/vhdl_designers_guide/what_is_vhdl/+what+is+VHDL%3F&cd=1&hl=en&ct=clnk&gl=us

Collection

2011 Northeast Section Meeting

Authors

Bhushan Dharmadhikari; Prabir Patra; Navarun Gupta; Lawrence V. Hmurcik

, “Electrical, rheological,morphological studies in co-continuous blends of polyamide 6 andacryonitrile/butadiene/styrene (ABS) with multiwall carbon nanotubes prepared by meltblending”, Composites Science and Technology 69, pp 365-372 (2009), available onlineat sciencedirect.com.[7] Q. Li, Y. Li, X. Zhang, S. Chikkannanavar, Y. Zhao, A. Dangelewicz, L. Zheng, S.Doorn, Q. Jai, D. Peterson, P. Arendt, and Y. Zhu, “Structure dependent electricalproperties of carbon nanotube fibers”, Advanced Materials 19, pp 3358-3363 (2007).[8] P. Poetschke, M. Abdel-Goad, I. Alig, S. Dudkin, D. Lellinger, “Rheological anddielectrical characterization of melt mixed polycarbonate-multiwalled carbon nanotubecomposites”, Polymer 45, pp 8863-8870 (2004), available online at

Collection

2014 ASEE Zone 1 Conference

Authors

Lile Yu; Jingyun Xiao; Xingguo Xiong; Prabir Patram

optimized designparameters, we can get the change volume of one diaphragm Fig 10. First vibration mode of middle membrane of micropumpin one cycle ∆V 1.371 10 L, if we assume 80HZ, (f0=377908Hz)flow rate of magnetic micropump in one cycle Q 4.3910 pL/s. VI. ANSYS SIMULATION ANSYS is an engineering simulation software. It is used tosolve mechanical problems such as static or dynamicstructural analysis, and electro-magnetic problems. Thedynamic analysis of this magnetic micropump predicts therelationship between device performance parameters andvarious design parameters (such as pump length, pump width,and pump thickness). However, those parameters are based onthe theoretical analysis. In order to

Collection

2014 ASEE Zone 1 Conference

Authors

John Finnie

Y total m (to flume bed) Y Area V avg V avg m (to Flow Treatment * Q gpm Q cms 3 6.5 10.5 cobbles) m2 m/s Slope Fr PIV V PIV/V avg A ae 5225 0.330 0.315 0.312 0.297 0.2235 0.447 0.738 0.0051 0.498 0.8044 1.091 A ag 5225 0.330 0.314 0.31 0.295 0.222 0.444 0.743 0.503 0.7044 0.949 A oe 5225 0.330 0.314 0.313 0.296 0.2235 0.447 0.738 0.498 0.6894 0.935 A og 5225 0.330 0.318 0.315 0.3 0.2265 0.453 0.728

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Kimberly T. Luthi, Embry-Riddle Aeronautical University - Worldwide; David Paul Harvie, Embry-Riddle Aeronautical University - Worldwide; John K Wilson, Embry-Riddle Aeronautical University - Worldwide; Monica Surrency, Embry-Riddle Aeronautical University - Worldwide

Tagged Topics

Diversity, Professional Papers

engineering-related fields. The questions also investigated how students were supported as they developedtheir identify with in the engineering community with an increased motivation to advance.Out of the responses to Q-1 (-ways you felt most supported and any areas for improvement in thepeer-led activities) 63% were positive. Similarly, positive comments made up 65% of responsesfor Q-2 (has the interaction with peers helped support your academic and career goals?) InVivowas used to code the reflective responses by themes.Positive Experiences with Peer Led ActivitiesAttitudes and interest towards engaging with peers was well supported through the first question.To answer the question, indicators around broader statements regarding the PLTL (Peer-Led

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Erin Bosarge, University of South Alabama

Tagged Topics

Diversity, Professional Papers

Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097[9] Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Shen, M. Q. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041[10] Rizvi, S., Waite, J., & Sentance, S. (2023). Artificial intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature review. Computers and Education: Artificial Intelligence, 4, 100145. https://doi.org/10.1016/j.caeai.2023.100145[11] Almatrafi, O., Johri, A., & Lee, H. (2024). A systematic review of AI literacy conceptualization, constructs, and implementation and

Collection

2008 ASEE Zone 1 Conference

Authors

Robert Dees; Ken S. Gilliam; Michael J. Kwinn

. This is alarge departure from traditional multiple-choice scoring.Many scoring rules have been developed, but three of the most popular (for n multiple choice questions)are: Quadratic (Q): Qi(r) = 2ri – r • r ∈ [− 1,1] (1) Spherical (S): ∈ [0,1] Si(r) = ri / (r • r) 1/2 (2) Logarithmic (L): Li(r) = ln(ri) ∈ (− ∞,0] (3)where ri is the probability assigned to the correct answer (i=1…n).7 2 As discussed by Bickel, the

Collection

2015 ASEE Zone 3 Conference

Authors

Francisco Lourenco; Nian Zhang; Sasan Haghani

(FSKD), 3, 2010, 1324 - 1327.[12] P. Bai, X. Song, J. Wang, W. Shi, Q. Wang, A Hillslope Infiltration and Runoff Prediction Model of Neural Networks Optimized by Genetic Algorithm, 2010 International Conference on Mechanic Automation and Control Engineering (MACE), 2010, 1256 – 1259.[13] J. Liu, B. Wang, Parameters Selection for SVR Based on the SCEM-UA Algorithm and its Application on Monthly Runoff Prediction, 2007 International Conference on Computational Intelligence and Security, 2007, 48 - 51.[14] W. Guo, H. Wang, J. Xu, Y. Zhang, BF Neural Network Model Based on Improved PSO for Predicting River Runoff, 2010 International Conference on Intelligent Computation Technology and Automation (ICICTA), 2, 2010, 968 – 971.[15] H

Collection

2025 Northeast Section Conference

Authors

Paul Cotae; Nian Zhang; Onyinye Obioha-Val

backscatter spectroscopy for standoff detection of trace explosives, “Optical Engineering, vol.59,no. 9,p.092009,2020.doi: 10.1117/1.OE.59.9.092009.[3] Chawla, Nitshe, Bowyer K, Hall L., Kegelmeyer W. “SMOTE: Synthetic Minority Over-Sampling Technique.” Journal of Artificial Research, vol.16, 2002, pp.321-357.[4] C.J. Breshike, C. A. Kendziora, R. Furstenberg, and R. A. McGrill, “Infrared backscatter imaging spectroscopy for standoff detection of trace explosive, “Journal of Applied Physics, vol.125, no.10, p.104901, 2019. doi:10.1063/1.5079622.[5] C.Liu, J. Li, M.E. Paoletti, J.M. Haut, A. Plaza and Q. Shi, “Accessibility-Free Active Learning for Hyperspectral Image Classification

Collection

2025 Northeast Section Conference

Authors

Shashi Kiran Chandrappa, Fairfield University; Sidike Paheding, Fairfield University

! 2n+1 X n X The Indian Pines dataset is a widely studied bench- f (x) = Φq ϕq,p (xp ) , (1)mark in HSI classification, captured using the Airborne q=1 p=1Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. The where ϕq,p and Φq denote the univariate inner and outerdataset was collected in a region of agricultural fields near functions, respectively. In KANs, each of these inner functionsNorthwestern Indiana, USA, and is particularly

Collection

2025 Northeast Section Conference

Authors

Shashi Kiran Chandrappa; Sidike Paheding; Yu Cai Cai

delimiters This is awesome! - Response: Positiveand retrieving key attributes, including method, URL, headers, This is bad! - Response: Negativeand classification labels. Headers are dynamically mapped Wow that movie was good! - Response: Positiveinto a structured format, and categorical labels are assigned What a horrible show! -numerical values (Normal → 0, Anamoly → 1). A combined Model Output Output: Negative 3) Chain of thought: Detailed roadmap for your LLM’s rea-soning journey. It explicitly lays out each step the LLM shouldtake, from identifying the question to analyzing informationand drawing conclusions. Model Input Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls

Conference Session

Research Methodologies – Session 2

Collection

2023 ASEE Annual Conference & Exposition

Authors

Neha Kardam, University of Washington; Shruti Misra, University of Washington; Denise Wilson, University of Washington

Tagged Divisions

Educational Research and Methods Division (ERM)

: Theme 3: Theme 4: Engineering Interactions 1 Interactions 2 Active Learning (Problem solving) (Office hours) (Q&A) (Experiential)While the importance of interactions between students and instructors is a critical element ofundergraduate education that is common to all fields and disciplines, the remaining two topicsthat emerged from topic modelling were more specific to engineering. Topic 1 emphasizedstudent preferences for more problem-solving time and practice with TAs. This relates directly tothe theme of problem-solving which is highlighted by the ABET (accreditation board forengineering and technology) student outcome #1: “an ability to identify

Collection

2018 ASEE Mid-Atlantic Section Spring Conference

Authors

Andrew Grossfield P. E., Vaughn College of Aeronautics & Technology

horizontal domain, and now we are positioned to observe something which isremarkable and wonderful.Take any point, P0 in the x-y plane and consider a point, P circling P0 at a fixed distance, dr, asshown below in figure 5. Watch the motion of the point, Q, in the tilted plane directly above P.Say the motion of P starts when Q is highest. Q will be observed to descend monotonically to aminimum and then rise monotonically back to its starting height.We can now derive the relationship between the height of the point Q and the angle that P makesin the x-y space. Since the gradient of a plane is constant and ⃗⃗⃗⃗ | is constant, equation 2 aboveleads to the conclusion that if the angle, φ, of the direction is chosen to be 0º in the uphilldirection, then

Conference Session

Balancing Act: Ideas in Pre- & Post- Surveys and Assessment of Professional Skills

Collection

2017 ASEE Annual Conference & Exposition

Authors

Simon Thomas Ghanat P.E., The Citadel; James Kaklamanos, Merrimack College; Suresh Immanuel Selvaraj, University of Evansville; Corrie Walton-Macaulay, Bucknell University; Matthew Sleep, Oregon Institute of Technology

Tagged Divisions

Civil Engineering

Conference Session

Mathematics Division Technical Session 4

Collection

2015 ASEE Annual Conference & Exposition

Authors

Peter Goldsmith P.Eng., University of Calgary

Tagged Divisions

Mathematics

rules for the addition, composition, and inversion of rational relations will now bestated and proved. The following theorem extends that given in 8 by adding a rule for the equalityof two rational relations. Also, the proof presented here uses relational identities.Theorem 10.2 The set of rational relations (Q, +, ·) is a subseminearring of L(C∞ ). For alla1 , a2 ∈ B, and all b1 , b2 , g ∈ B\{0}, a1 ga2 a1 a2 coprime(b1 , a2 ) ⇒ = , (43) b1 g b2 b1 b2 a1 a2 a1 b2 + a2 b1 coprime(b1 , b2

Conference Session

Experiences in Teaching Energy Courses

Collection

2007 Annual Conference & Exposition

Authors

Brendan Egan, Milwaukee School of Engineering; Stephen Dechant, Milwaukee School of Engineering; Christopher Damm, Milwaukee School of Engineering

Tagged Divisions

Energy Conversion and Conservation

, and to exhaust) wasdetermined. ⋅ 28.7 kW Q amb = = 0.082 = 8 percent 348.5 kW ⋅ 76.3 kW Q cooling = = 0.2189 = 22 percent 348.5 kW ⋅ 115 kW E elec = = 0.3299 = 33 percent 348.5 kW ⋅ 128 kW Q exhaust = = 0.367 = 37 percent 348.5 kWThese percentages were used in the EES model in order to calculate the heat flow to each areawhen the system electrical output was modified.Using the EES model, the following table was constructed to detail the electrical energygenerated and heat load provided by the exhaust gas boiler for different engine loads. Table 2

Collection

2018 ASEE Conferences - Conference for Industry and Education Collaboration / San Antonio proceedings

Authors

Andrew Grossfield

might have more thanone value for any of the variablesOn the other hand, an explicit form of the same relationship z = √25 − x 2 − y 2 is a functionalform with the range being along the vertical z axis and the domain lying in the horizontal x-yplane. If the operations in the function are single-valued then so will be the surface in the x-y-zspace. In the next section we will examine the slopes of a tilted plane, z = Ax + By + C above acircle in the x-y horizontal domain, and now we are positioned to observe something which isremarkable and wonderful.Take any point, P0 in the x-y plane and consider a point, P circling P0 at a fixed distance, dr, asshown below in figure 5. Watch the motion of the point, Q, in the tilted plane directly above P.Say

Conference Session

Improving Multidisciplinary Engineering Education

Collection

2005 Annual Conference

Authors

Teresa Mayes; John Bennett

as an issue in the EAC portion ofthe 2003 Annual Report2 which states that “Activities were undertaken to address training ofevaluators, consistency issues, feedback on program evaluators and team chairs…..”Q. 3 Role of the College in AccreditationWhen asked about the role of the college in the assessment and accreditation process, the fourmost commonly cited roles were: a) Coordinating a team of ABET coordinators which shared best practices (17 respondents); b) Coordinating and/or administering various surveys, including alumni, senior and/or employer surveys (15 respondents); c) Completing the Appendix II document (10 respondents); and d) Gathering the support information and/or assessing core courses and general education

Conference Session

MECH - Technical Session 9: Advanced Mechanical Engineering Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Rachel Mok, Massachusetts Institute of Technology; Cong Li, Massachusetts Institute of Technology; Benita Comeau, Massachusetts Institute of Technology; Emily Welsh, Massachusetts Institute of Technology; Nicholas Xuanlai Fang, University of Hong Kong; John Liu, Massachusetts Institute of Technology

Tagged Divisions

Mechanical Engineering Division (MECH)

cognitive learning gains be-tween the simulation and paper format groups. The simulation and paper cohorts each consistedof 18 students, when the data is combined across the Spring and Fall semesters.Figure 6: Learner preferences. The statements that learners are prompted to rank in the learnerpreference survey are displayed above each histogram. Learners from both the simulation andpaper cohorts strongly favored the simulation learning format over the paper learning format.5.1 Learner PreferencesThe results for the learner preferences survey are shown in Fig. 6. To examine if there were anypotential bias due to the order in which students completed the formats, we first conducted nor-mality checks using the Shapiro-Wilk test (αSW = 0.05) and Q-Q

Conference Session

Frontiers in EM Education

Collection

2011 ASEE Annual Conference & Exposition

Authors

Ertunga C. Ozelkan, University of North Carolina, Charlotte; Agnes Galambosi, University of North Carolina, Charlotte

Tagged Divisions

Engineering Management

Introductions at thebeginning of a semester, HW assignments, Discussion Questions, usage of course Calendar, Q/AForum, term Projects, posting Slides, conducting Quizzes, showing Industry Videos (or softwaredemonstrations) and usage of Chat, which all received scores 4 or higher. Page 22.1151.8 Ranking of Online Tools and Practices 5 4.8 4.7 4.7 4.6 4.5 4.5 4.4 4.4 4.2 4.1 4.1 4.0 4.0 3.8 4

Conference Session

Best of Computer in Education Division

Collection

2013 ASEE Annual Conference & Exposition

Authors

Jacob Bishop, Utah State University; Matthew A Verleger, Embry-Riddle Aeronautical Univ., Daytona Beach

Tagged Divisions

Computers in Education

Activities Treatment Control Type Structure Full Flip, Single-Group Lage [48,49] Fr SGA VL 40 - O O-X Kaner [44] U SGA VL - - O O-X Bergmann [5,6] HS - - - - - - Talbert [70] U SGA;Q VL 7 - O O-X Gannod [28,29] Fr-Gr HW;SGA VL 20;160 IP - O X-X Toto [74] Jr - VL;Q 74 - O X1 -X2 Zappe

Collection

2001 Annual Conference

Authors

James Masi

indielectric studies of different materials [1-4]. The details of the spectrometer can be found inthose references in which dielectric relaxation mechanism has been studied using a resonant Page 6.666.23cavity in T011 mode. The main purpose of using this mode is because of a very high Q-value forthe resonant cavity. This makes the cavity very sensitive in terms of its perturbation of electricfield. Similar techniques using resonant cavities in different modes have also been used [5-9].A computer control system is used to monitor the temperature of the microwave resonant cavityvery precisely.II. Theory, Procedure, and AnalysisDielectric behavior of a

Conference Session

First Year Programs Division Poster Session: The Best Place to Really Talk about First-Year Education

Collection

2015 ASEE Annual Conference & Exposition

Authors

Mary E. Goodwin, University of South Florida; John Pharo Morgan III, University of South Florida; Yan Wang, University of South Florida; Michelle King, University of South Florida College of Engineering; Blake A Burton, University of South Florida

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

Conference Session

Software Engineering Division Technical Session 2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Gregory Kulczycki, Virginia Tech; Steven Atkinson, Virginia Tech

Tagged Divisions

Software Engineering Division

attend, where we typically do a partial walkthrough of the currentassignment and answer questions. If students cannot attend the Q&A session, they are required towatch the recording. If the students have questions that the live Q&A does not answer, they canpost their questions to Piazza (an online Q&A forum), which both instructors check at least oncea day. Students are encouraged to make their posts public and answer other student questions.Posting code is discouraged.Model Project and Course ProjectWhen this course was first designed, the professor’s knowledge of web development waslimited, so he used an online tutorial – the NetBeans e-commerce tutorial [14] – as a basis for thecourse project. The tutorial was well-written, and it

Conference Session

Architectural Engineering Division (ARCHE) Technical Session 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

Keith E. Hedges, Drury University

Tagged Divisions

Architectural Engineering Division (ARCHE)

- copycats[5] Rogers v. Koons, 960 F. 2d 301 - Court of Appeals, 2nd Circuit 1992, Available: https://scholar.google.com/scholar_case?case=9102865469766650757&q=rogers+v+koons &hl=en&as_sdt=6,26[6] R. Metz, “AI Won an Art Contest, and Artists are Furious,” CNN Business, September 3, 2022 [online]. Available at: https://www.cnn.com/2022/09/03/tech/ai-art-fair-winner- controversy/index.html[7] C. Valance, “Art is Dead Dude: The Rise of AI Artists Stirs Debate,” BBC News, September 13, 2022 [online]. Available: https://www.bbc.com/news/technology-62788725[8] U.S. Copyright Office, Circular 14, Copyright in Derivative Works and Compilations, July 2020 [online]. Available: https://copyright.gov

Conference Session

Curricular Innovations in Computing - 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

David H. K. Hoe, Loyola University Maryland; Mary Lowe, Loyola University Maryland; Dave Binkley, Loyola University Maryland

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

public-key cryptosystems, such as RSA, could beefficiently broken. In these systems information is encrypted using a number N = pq, where pand q are two large primes. The information is decrypted with knowledge of p and q. Thesecurity of the encryption depends upon the extreme difficulty in factoring N. Shor’s algorithmstimulated the growth of the QC industry. Because this algorithm has a number theory part and aQC part, it takes a significant effort to understand and implement it without predefined functionson a simulator. One of the authors of this paper therefore worked on simulating Shor’s algorithmwith an undergraduate physics major during the summer. The student had no prior knowledge ofQC. We were able to factor 91=13×7 on the student PC

Conference Session

Community Engagement Division 1 - Empowering Students and Strengthening Community Relationships

Collection

2023 ASEE Annual Conference & Exposition

Authors

Hannah Cooke, University of Connecticut; Rebecca Campbell-Montalvo, University of Connecticut; Todd Campbell, University of Connecticut; Chester Arnold; Maria Chrysochoou, University of Connecticut; Byung-Yeol Park, University of Connecticut; Peter C. Diplock

Tagged Topics

Diversity

Tagged Divisions

Community Engagement Division (COMMENG)

, pp. 573–593, Dec. 2019, doi: 10.1007/s12564-019-09580-6.[3] S. E. Dempsey, “Critiquing community engagement,” Manag. Commun. Q., vol. 24, no. 3, pp. 359–390, 2010, doi: 10.1177/0893318909352247.[4] T. D. Mitchell, “Traditional vs. Critical Service-Learning: Engaging the Literature to Differentiate Two Models,” Mich. J. Community Serv. Learn., vol. 14, no. 2, pp. 50–65, 2008.[5] M. Checker, “‘But I Know It’s True’: Environmental Risk Assessment, Justice, and Anthropology,” Hum. Organ., vol. 66, no. 2, pp. 112–124, Jun. 2007, doi: 10.17730/humo.66.2.1582262175731728.[6] R. Holifield, “Environmental Justice as Recognition and Participation in Risk Assessment: Negotiating and Translating Health Risk at a Superfund

Conference Session

Civil Engineering Division - Mechanics Applied and the Best in Five... Get Ready!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Harry Cooke, Rochester Institute of Technology (CET)

Shear in a Transversely-Loaded BeamIn strength of materials, students learn about shear forces that develop on horizontal planes in atransversely-loaded beam due to variations in internal bending moment along the beam lengthcaused by that loading. The shear force on a horizontal plane is often quantified per unit lengthof the beam using the shear flow, q, calculated using the formula: q = VQ/Iwhere V is the internal vertical shear force at a particular location along the beam length, I is themoment of inertia of the beam cross-section (perpendicular to the length), and Q is the firstmoment of area (about the centroidal axis) of the cross-section segment isolated by the horizontalplane. Students learn

Conference Session

NSF Grantees Poster Session

Collection

2022 ASEE Annual Conference & Exposition

Authors

Brian Skromme, Arizona State University; Srividya Bansal, Arizona State University; Rishabh Gupta, Arizona State University; Tariq M Nasim, Arizona State University; Caleb Redshaw; Benjamin Miller, Arizona State University; Petru Andrei, Florida A&M University - Florida State University; Hector Erives, University of Texas at El Paso; Deanna Bailey, Morgan State University; Gregory Wilkins, Morgan State University; Megan O'Donnell, Arizona State University; Wendy Barnard, Arizona State University

large classes,” IEEE Trans. Educ., vol. 48, pp. 658-663, 2005.[7] P. Marepalli, A. Magana, M. R. Taleyarkhan, N. Sambamurthy, and J. V. Clark, “SugarAid 0.2: An online learning tool for STEM,” in Proc. 2010 Internat. Conf. Computat. Intell. and Software Engrg, 2010, pp. 1-6.[8] N. Sambamurthy, A. Edgcomb, and Y. Rajasekhar, “Student usage of interactive learning tools in an online linear circuit analysis textbook,” in Proc. 2019 IEEE Frontiers in Educat. Conf., 2019, pp. 1-6.[9] K. VanLehn, “The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems,” Educat. Psychologist, vol. 46, pp. 197-221, 2011.[10] C. D. Whitlatch, Q. Wang, and B. J. Skromme, “Automated