Multiple Tutors Research Articles

Artificial Intelligence Technologies for Teaching and Learning in Higher Education

The term “Artificial Intelligence” (AI) refers to the simulation of human intelligence on a computer. Higher education can benefit from AI because it is a computationally efficient paradigm. Learning adapted to the changing demands of students is one of the key educational advantages of AI. Students can modify the pace of a course to better competency. Poor faculty and teaching quality and a general lack of motivation and interest among students are among the difficulties facing higher education. An artificial intelligence-assisted integrated teaching–learning framework (AL-ITLF) for higher education is proposed in this research. Multiple tutoring services are also involved in the curriculum, which is skill-based. The extreme learning machine (ELM) technique evaluates designs integrated into the suitable student monitoring model weighted score (WS) and exam results. An educational model that is more efficient, adaptable, and effective than current traditional education has been developed due to AI research in higher education. Higher education’s use of AI has resulted in a more efficient, adaptive, and effective educational model than traditional schooling. High accuracy, higher performance, lower processing costs, and a high prediction and low error rate are advantages of the suggested AI-ITLF approach. The WS and exam results were evaluated using an ELM algorithm as part of a proper student monitoring model.

The Impact of Undergraduate Tutor System in Chinese 8-Year Medical Students in Scientific Research.

PurposeThis study aimed to evaluate the effect and influence of the undergraduate tutor system on the undergraduate stage of Chinese 8-year medical program students in scientific research.MethodsWe collected related data from 194 medical students in the Xiangya Medical School of Central South University. The questionnaire was composed of three parts, namely, eight questions for basic information about individual and undergraduate tutor system, five questions for the subjective feeling impact of the undergraduate tutor system, and 22 questions for accessing the scientific research ability and academic results. The students were mainly divided into three groups to compare different kinds of undergraduate tutor systems, namely, single tutor for multiple students' system (group A), multiple tutors for multiple students' system (group B), and no tutor system for comparison (group C).ResultsThe type of tutorial system, the frequency of guidance, and the way of guidance were independent influence factors of the view of 8-year medical students on scientific research. Group B behaved better than group C in literature processing (P = 0.012), experimental operation (P < 0.001), statistical analysis (P < 0.001), and manuscript producing (P = 0.019). Group A and B joined in more National college students' innovation and entrepreneurship training programs (P = 0.003, P < 0.001). The most popular types of articles published by students were bioinformatics, meta-analysis, and reviews.ConclusionUndergraduate tutor system has made tremendous achievements in cultivating students' scientific research capacity; however, implement improvement should be considered to better educate students.

IIoT Talent Cultivating Mechanism in line with Industrial Internet

Industrial Internet or Industry 4.0 has been a national development strategy. Keeping up with the development, lecturers and teachers have upgraded and improved the teaching effectiveness, efficiency, and productivity. However, there is lack of a comprehensive talent cultivating mechanism currently. Sichuan University and others took industrial big data analysis &application and cyber-security as the characteristic example of Industrial Internet of Things, formulated the undergraduate talent cultivating program, curriculum system and compiled relevant textbooks. The universities also explored the development mechanism of interdisciplinary integration, the cooperative education mechanism of multiple tutors and a multiple consultants’ system to strengthen the faculty. Then, a multi-level interdisciplinary talent training mechanism for the Industrial Internet of Things has been formed, providing an example for other disciplines.

Use of Visual Dashboards to Enhance Pharmacy Teaching.

Teaching large cohorts of pharmacy students with a team of multiple tutors in a feedback intensive course poses challenges in relation the amount of data generated, data integrity, interpretation of the data and importantly application of the insights gained from the data. The dispensing and counselling course in the third year BPharm at the University of Sydney has implemented the USyd Pharmacy Dashboard, developed to address these challenges following the Technological Pedagogical Content Knowledge Framework (TPACK) to integrate technology into teaching. The dashboard was designed to improve the student experience through more consistent feedback, gain insights to improve teaching delivery and provide efficiencies in maintaining data integrity. The tool has been developed using an action-based research approach whereby ideas are put into practice as the means to further develop the idea and improve practice. Refinement of the USyd Pharmacy Dashboard over three years has shown improvements in teaching delivery as teachers can respond to emerging trends. Student performance and satisfaction scores have increased, mainly due to improved consistency between tutors and improved delivery of feedback. Time involved with administrative tasks such as data maintenance is reduced. Opportunities for further refinements such as real time benchmarking and developing an open learner model have become apparent.

Divide y vencerás: Efectos de dos intervenciones para el aprendizaje interactivo en grupos grandes de estudiantes sobre la percepción de la calidad del ambiente de aprendizaje

IntroductionLittle is known on the effect of different forms of division of a large group of students for the interactive discussion of cases, on the quality of the learning environment. We aim to compare two types of division in the face-to-face component of an inverted classroom in surgery. MethodsFor eighteen weeks, Group-1 was divided into eight small groups within the same physical classroom, under the simultaneous supervision of four tutors. Group-2 was divided into eight small groups distributed in four independent physical classrooms (2 groups/classroom), under the supervision of one tutor in each classroom. The quality of the learning environment was evaluated with the DREEM questionnaire. The effects of each division on the global DREEM score and its domains were evaluated with the d (Cohen) test. ResultsThe overall DREEM score was: 145.01±2.17 (Group-1) versus 131.46±18.48 (Group-2) (p<0.05). The magnitude of the effect of division of the Group-1 on the DREEM score was d=0.66. All DREEM domains were superior in Group-1 (p<0.05), as well as the effects on the quality of the environment. ConclusionsThe effects on the learning environment are greater when a large group is divided into small groups that are supervised by multiple tutors in the same physical classroom, compared with a large group that is divided into small groups that are supervised by a single tutor in separate classrooms.

Comparing machine learning to knowledge engineering for student behavior modeling: a case study in gaming the system

ABSTRACTLearning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of a case study in building models able to detect when students “game the system”, a behavior in which learners abuse the environment’s support functionalities in order to succeed by guessing or copying answers. We compare the predictive performance, interpretability and generalizability of models created using each approach, doing so across multiple intelligent tutoring systems. In our case study, we show that the machine-learned model required less resources to develop, but was less interpretable and general. In contrast, the knowledge engineering approach resulted in the most interpretable and general model. Combining both approaches in a hybrid model allowed us to create a model that performed best across the three dimensions, but requiring increased resources to develop.

Medical Students\u2019 Views About Having Different Types of Problem-Based Learning Tutors

BackgroundAt Norwich Medical School, Year 3 or 4 medical students taking a year out of the 5-year undergraduate MBBS degree to do a master’s degree in clinical education worked as near-peer problem-based learning (PBL) tutors for students in Year 2. Peer-assisted learning has been shown to benefit both peer tutors and tutees; in this study, experiences of students with near-peer PBL tutors were compared to students with other types of PBL tutor.MethodsUsing existing student evaluation data, we compared student views about PBL tutor performance, PBL group functioning, and overall satisfaction with PBL learning experience according to whether their PBL tutor/s were (1) a single near-peer tutor (later-year MB BS student), (2) a single staff tutor, (3) multiple staff tutors, or (4) multiple newly qualified doctor tutors.ResultsResults indicated that students’ evaluation of tutor performance was more positive for near-peer PBL tutors compared to both groups of staff tutors for most areas evaluated. Additionally, students’ evaluation of overall satisfaction with PBL was more positive for near-peer PBL tutors compared to multiple staff tutors. Tutor performance for multiple staff tutors was evaluated less positively compared to both single staff and multiple newly qualified doctor groups. But there were no statistically significant differences between the four groups regarding PBL group functioning.ConclusionNear-peer PBL tutors perform comparably or better to staff PBL tutors in salient measures of tutor performance and group functioning. We conclude that medical students find near-peer PBL tutors to be an acceptable addition to the PBL tutor workforce.

Multiple Literacy Tutoring Experiences across a Teacher Preparation Program: How Can Practice in Hybrid Spaces Challenge the “Practice Makes Practice” Dilemma?

ABSTRACTThe current qualitative study addresses the growing concern in preservice teacher (PT) education that simply increasing the amount of field experiences in teacher preparation programs may just reinforce the status quo in teaching. The focus in this report is on how a series of literacy tutorials, designed as hybrid spaces for learning, provide opportunities for PTs to experience practices that are not highly present or visible in elementary classrooms as a result of pressures to standardize the literacy curriculum. Although literacy tutorials are fairly common in teacher preparation programs, multiple literacy tutorials coordinated across a preparation program are rare. In this research project the authors focused on the learning of PTs across multiple tutorial experiences and the ways in which these tutorial experiences, as hybrid spaces, created opportunities for PTs to experience powerful teaching in ways that may not be present in traditional classrooms and in traditional practicum experiences. The findings from the current study document the ways in which the multiple tutoring experiences in multiple tutoring experiences supported the PTs in their growing understanding, engagement, and reflection around practices that challenge the standardized literacy curriculum shaping schools today.

The Study on the Multiple Agent-Based Independent and Collaborative Intelligent Tutoring System Model

Over the years, the traditional computer-assisted teaching can not meet the needs of university teaching, the traditional teaching system software, most of the existence of low intelligence, lack of teaching strategies and other shortcomings.Multi-AGENT technology and intelligent tutoring systems is the current research focus in computer intelligence education. Integrating multi-Agent features and multi-Agent application theories in ITS, this paper proposes a multiple Agent-based intelligent network tutoring system design model, detailedly analyzes the functions of each layer in the system, and presents system database category design and system model features.

Identification and definition of lexically ambiguous words in statistics by tutors and students

Lexical ambiguity arises when a word from everyday English is used differently in a particular discipline, such as statistics. This paper reports on a project that begins by identifying tutors’ perceptions of words that are potentially lexically ambiguous to students, in two different ways. Students’ definitions of nine lexically ambiguous words are also collected at the beginning and end of a semester of introductory statistics study, in a complex design taking account of multiple tutors and multiple words in multiple contexts. Tutor perceptions and actual student difficulties at the beginning of a semester are compared. The lexical ambiguity associated with the word ‘significance’ is shown to be evident in students even after completing an introductory statistics course.

Math Is Not a Spectator Sport: The Effect of Online Homework-Completion Tutoring On Community College Remedial Mathematics Performance

This article analyzes the findings from an 18-section experiment studying the effect of homework-completion tutoring on community college students’ remedial mathematics performance. The experiment involved 529 students registered for two remedial math courses: math skills and algebra. For each course, the experiment studied nine sections: three experimental with multiple tutors for online homework, three control with a single tutor for online homework, and three control with a single tutor for pencil-and-paper exercises. While state budget constraints delayed the availability of tutors for the experimental group until midway through the semester, that group outperformed the pencil-and-paper group at a 0.05 significance level, while the performance of the online homework control group categories surpassed those of the corresponding pencil-and-paper categories at up to a 0.001 significance level. In addition, for each course, math lab attendance for both the experimental and control online homework cohorts surpassed that of the pencil-and-paper cohorts. These results corroborate and extend earlier research and show the importance of active problem-solving rather than passive absorption in increasing remedial mathematics performance.

Statistical and Prosodic Cues for Song Segmentation Learning by Bengalese Finches (Lonchura striata var. domestica)

AbstractJuvenile songbirds learn their songs from adults. Birds do not simply learn songs verbatim but they sometimes learn parts of songs from multiple tutors and recombine these into one song sequence. How they segment a particular part and select that as a chunk and how these chunks are recombined are interesting questions to ask, because such segmentation and chunking is also considered to be a basic mechanism in human language acquisition. The song of the Bengalese finch has a complex syntax with variable note‐to‐note transition probabilities and could thus be suitable for the study of segmentation and chunking in birdsong. Thirty‐two male Bengalese finch chicks were reared in a large aviary where 11 adult tutors and 10 adult females were breeding freely. In this environment most male chicks learned songs from several tutors. The song note‐chunks that juveniles copied had higher transition probabilities and shorter silent intervals than did the boundaries of the chunks, suggesting that Bengalese finches segment songs using both statistical and prosodic cues. Thus, the Bengalese finch could prove to be an excellent model in which to study neural and behavioral mechanism for sound segmentation.

Educators' perceptions of automated feedback systems

&lt;span&gt;Assessment of student learning is a core function of educators. Ideally students should be provided with timely, constructive feedback to facilitate learning. However, provision of high quality feedback becomes more complex as class sizes increase, modes of study expand and academic workloads increase. ICT solutions are being developed to facilitate quality feedback, whilst not impacting adversely upon staff workloads. Hence the research question of this study is 'How do academic staff perceive the usefulness of an automated feedback system in terms of impact on workloads and quality of feedback?' This study used an automated feedback generator (AFG) across multiple tutors and assessment items within an MBA course delivered in a variety of modes. All academics marking in the course completed a survey based on an adaptation of the &lt;/span&gt;&lt;em&gt;unified theory of acceptance and use of technology&lt;/em&gt;&lt;span&gt; (UTAUT) model. Results indicated that while the workload impact was generally positive with savings in both cost and time, improvements and modifications to the system could further reduce workloads. Furthermore, results indicated that AFG improves quality in terms of timeliness, greater consistency between markers and an increase in the amount of feedback provided.&lt;/span&gt;

Syllable chunking in Bengalese finches in a multi-tutor environment

Experiments in birdsong learning have traditionally involved one tutor, usually the father, and the proportion and accuracy of note copying are discussed as indexes of song learning. But in the wild, there are several conspecific males around song-learning pupils. To test song learning under naturalistic situation, 11 male and ten female Bengalese finches were kept in a large flight cage containing ten pot-shaped nests. Seventy-eight chicks were born in this aviary over an 18-month period. We recorded the full songs of male birds after they had matured, and compared the songs between offspring and the original adult males. Most of them learned their songs from one or two tutors and some learned from three or four tutors. When a bird learned from multiple tutors, each of these tutor songs was copied in chunks and within a chunk the order of the song elements was the same as that observed in the tutor male. Furthermore, Bengalese finches change the order of chunks as they sing, and it was possible to express the rule using a finite-state syntax. Therefore, Bengalese finches have an innate universal grammar allowing them to construct a finite-state syntax from multiple sources. [Work supported by JSPS and JST.]

Sequential Learning From Multiple Tutors and Serial Retuning of Auditory Neurons in a Brain Area Important to Birdsong Learning

Songbirds hear many vocal models during a juvenile sensitive period, transiently imitating some while retaining imitations of others in their repertoires. Despite subsequent conflicting experiences, early experience can exert lasting effects on neural structure and function, raising the possibility that transiently expressed vocalizations or their relevant models are stored in the adult songbird's brain. One site where learned song representations could be stored is the lateral magnocellular nucleus of the anterior nidopallium (LMAN), which in the adult songbird contains neurons responsive to playback of the bird's own song (BOS) and the tutor song (TS). To test whether LMAN neurons develop and retain responses to transiently learned songs, we exposed zebra finch hatchlings [posthatch day 0 (PHD0)] to a first TS (TS1) for about 30 days, isolated them for about 30 days, then exposed them to a second TS (TS2) for 30 days starting at PHD 60. Behavioral analysis showed that PHD 60 juveniles had started to copy TS1, although this copying was transient, because the adult BOS resembled TS2 and not TS1. We found that LMAN auditory responses paralleled these behavioral changes: LMAN neurons at PHD 60 responded strongly and selectively to both the juvenile BOS and TS1, whereas LMAN neurons in adults responded to the adult BOS and TS2, but not to the transiently learned song or its model. Therefore LMAN auditory responses can be lost or overwritten as the juvenile copies a new song, suggesting that the adult LMAN does not store information about transiently learned songs or their models.

A model of multitutor ontology-based learning environments

The paper proposes the M-OBLIGE model for building multitutor ontology-based learning environments. The model is based on local ontologies, describing the domain of each individual tutor in the environment, and external ontologies, describing more general concepts. The ontologies are used by ontology processors to decide which tutors might benefit a student who needs to learn new concepts. The model allows domain expertise to be shared, and can be used as a framework for integrating multiple tutors on the web. We show how the model can be applied to tutors in the database domain. We also illustrate the process of developing the ontologies for an existing system.

Microgeographic song variation in island populations of the white-crowned sparrow (Zonotrichia leucophrys nutalli): innovation through recombination

AbstractCurrent geographic variation in bird song dialects may be used to infer historical processes involved in dialect formation. Discrete island populations, separated by water or unsuitable habitat, may be particularly useful as they allow for unequivocal subdivision of populations. We analyzed song recordings of nine populations of the white-crowned sparrow within the San Francisco Bay area, both on 'true' islands separated by water and in habitat islands along the Bay shore. We found one or two unique songtypes in each population with little variation within songtypes among individuals. Differences in songtypes concerned variation in syntax, syllable shapes, and spectral and temporal features. While each songtype exhibited unique features, there were often parts of the song that showed high similarity with songtypes of neighboring populations. We think that successfully dispersing males may learn from multiple tutors and produce songtype hybrids which could explain the variation in songtypes among populations. We found rare acoustic features on the 'true' islands, but also an apparent lack of impact by water barriers on the relationship between song similarity and geographic distance. A possible explanation may be that male dispersal, or just spread of song characteristics, is predominantly from island to mainland. Such a unidirectional pattern could result in rare song characteristics on islands, while general acoustic characteristics are still shared with the nearest mainland populations. Variation in similarity-based clustering of songtypes suggested that new songtypes emerge through recombination of components from existing songtypes.

Was it good for them? Reflections on the use of MENTOR and changes in course design using general performance measures

This paper considers the use of general performance measures in evaluating specific planning and design decisions in higher education and reflects on the students' learning process. Specifically, it concerns the use of the MENTOR multimedia computer aided learning package for helping students learn about OR as part of a general business degree. It includes the transfer of responsibility for a learning module to a new staff member and a change from a single tutor to a system involving multiple tutors. Student satisfaction measures, learning outcome measures and MENTOR usage patterns are examined in monitoring the effects of the changes in course delivery. The results raise some questions about the effectiveness of general performance measures in supporting specific decisions relating to course design and planning.

Social influences during song development in the song sparrow: a laboratory experiment simulating field conditions

Oscine songbirds are exposed to many more songs than they keep for their final song repertoire and little is known about how a bird selects the particular song(s) to sing as an adult. We simulated in the laboratory the key variables of the natural song learning environment and examined the song selection process in nine hand-reared male song sparrows,Melospiza melodia , a species in which males sing 5–11 song types. During their second and third months (their presumed sensitive period), subjects were rotated equally among four live adult male tutors that had been neighbours in the field. Tutors were housed in individual aviary ‘territories’ in four corners of the roof of a building; subjects could see only one tutor at a time, but they could hear the others at a short distance. Later in their first year (months 5–12), half the subjects were again rotated among all four tutors and the other half were randomly stationed next to just one tutor. Results from this experiment confirm and extend the findings from our two previous field studies of song learning in this species. Young males in this experiment (1) learned whole song types, (2) learned songs from multiple tutors, (3) preferentially learned songs that were shared among their tutors, (4) learned songs that other young males in their group also chose, and (5) learned more songs from the tutor they were stationed next to during the later stage (stationary subjects). These last two results support the late influence hypothesis that interactions after a bird's sensitive period affect song repertoire development.

Ecological correlates of song learning in song sparrows

Most studies of song learning have been conducted in the laboratory, and thus little is known about how song learning is affected by ecological variables in nature. Taking an ecological perspective, we studied song learning and territory establishment in a sedentary population of song sparrows (Melospiza melodia). We examined the song repertoires of an entire cohort of males (41 subjects) hatched in 1992 and compared them to those of potential song tutors (adults who were present in the young birds’ first year). We found that a young bird learns songs from multiple tutors who were neighbors in his first year and usually establishes a territory among or near these tutors. The degree to which tutors influenced the repertoires of the young birds varied greatly. Adult males who survived into 1993 tutored more songs than those who did not survive, supporting the hypothesis that a young male’s repertoire is influenced by social interactions with adults continuing beyond the classical sensitive period of the natal summer. The final repertoire of a young bird in most cases was weighted toward one of his tutors with whom he continued to interact, as an immediate neighbor, into his first spring. We found no correlations between potential measures of male quality or vigor and degree of tutor influence.