UPEI Moodle

Understanding, valuing and leveraging the critical aspects around
diversity and inclusivity, including equity and reconciliation are essential abilities required to address the challenges present in business today. Now more than ever, global leaders and those who aspire to become effective global leaders (regardless of managing people), must be equipped to create environments that support, enhance and foster such behaviors beyond fulfilling written and unwritten quotas and mandates.

A key area to explore will include expanding traditional definitions of diversity, inclusion and advocacy. Extensive practical application will provide an opportunity to gain knowledge, comfort and confidence in simulated real life work situations.

This course is also designed to support the development of key interpersonal, critical thinking, and emotional intelligence skills.


09-01-2024-23-04-2024 Lecture Tuesday 06:00PM - 08:50PM, McDougall Hall, Room 329

Current theoretical and conceptual frameworks in the field of early years education and how they inform current approaches to the children's learning from age 0-8 will be examined. Participants will study play and its major role in young children's learning, major influences affecting learning and play, methods of observing and studying play, and practical approaches for supporting and facilitating children's learning in early childhood settings and in grades K-2. Participants in current BEd programmes and educators from early years settings will develop projects combining their observations in early years settings with practical curriculum activities. 09-01-2024-08-02-2024 Lecture Tuesday, Thursday 01:00PM - 03:50PM, Memorial Hall, Room 308

This upper level reading course further develops students' ability to decode vocabulary and critically analyze academic text. 09-01-2024-25-04-2024 Lecture Tuesday, Thursday 02:30PM - 03:45PM, Bernardine Hall, Room 240

Additional class for Level 7 Academic Writing. 09-01-2024-25-04-2024 Lecture Tuesday, Thursday 11:30AM - 12:45PM, Bernardine Hall, Room 240

This course continues MATH 2610 with further concepts and theory of linear algebra. Topics include vector spaces, orthogonality, Gram-Schmidt Process, canonical forms, spectral decompositions, inner product spaces and the projection theorem. Three lecture hours a week. 09-01-2024-25-04-2024 Lecture Tuesday, Thursday 10:00AM - 11:15AM, Health Sciences Bldg, Room 106

This course is a continuation of Education 4320, in which students use language arts outcomes, materials, methods, and assessment techniques to design comprehensive literacy programs and activities. 09-01-2024-08-02-2024 Lecture Tuesday, Thursday 01:00PM - 03:50PM, Memorial Hall, Room 417

This course allows students to continue to explore the theoretical foundations and practices in the field of literacy. Students build their understanding of reading and writing processes by exploring the characteristics, needs, and practices that are unique to learners who are in the process of becoming autonomous or advanced on the development continuum of readers and writers. Students continue to learn the components of an effective literacy program, including those that allow for instructional differentiation, such as writing and reading workshops and reading circles/clubs. In addition, students appropriate practices and resources that develop literacy skills and competencies across subject areas. 09-01-2024-08-02-2024 Lecture Tuesday, Thursday 01:00PM - 03:50PM, Robertson Library, Room 208

This course is a study of the mathematics of survival models and includes some examples of parametric survival models. Topics include: tabular survival models, estimates from complete and incomplete data samples, parametric survival models, and determining the optimal parameters. Maximum likelihood estimators, derivation and properties, product limit estimators, Kaplan-Meier and Nelson-Aalen, credibility theory: limited fluctuation; Bayesian; Buhlmann; Buhlmann-Straub; empirical Bayes parameter estimation; statistical inference for loss models; maximum likelihood estimation; the effect of policy modifications; and model selection will also be discussed. Three lecture hours per week plus a one hour lab per week. 08-01-2024-24-04-2024 Lecture Monday, Wednesday, Friday 12:30PM - 01:20PM, Health Sciences Bldg, Room 103

Machine learning is the study of mechanisms for acquiring knowledge from large data sets. This course examines techniques for detecting patterns in sets of uncategorized data. Supervised and unsupervised learning techniques are studied, with particular application to real-world data. Three lecture hours per week. 09-01-2024-25-04-2024 Lecture Tuesday, Thursday 02:30PM - 03:45PM, Health Sciences Bldg, Room 104