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\Life skills education focuses on equipping individuals with the abilities needed to navigate everyday challenges and lead fulfilling lives. It encompasses a range of psychosocial and interpersonal skills that enable informed decision-making, effective communication, and healthy relationships. This type of education goes beyond traditional academic subjects, emphasizing practical skills applicable to personal, social, and professional contexts. 



 




 


Key aspects of life skills education include:







Developing self-awareness and emotional intelligence:
Understanding one's own emotions and those of others, managing stress and anxiety, and building healthy relationships are crucial components. 



 















 









Enhancing critical thinking and problem-solving:
Learning to analyze information, identify problems, and develop effective solutions is essential for navigating complex situations. 



 












 








Improving communication and interpersonal skills:
Effective communication, both verbal and nonverbal, is vital for building strong relationships and resolving conflicts. 



 












 








Promoting decision-making and goal-setting:
Learning to make informed decisions, set realistic goals, and develop plans to achieve them are important life skills. 



 












 








Fostering adaptability and resilience:
Developing the ability to adapt to change, cope with setbacks, and bounce back from challenges is essential for navigating life's ups and downs. 



 












 








Encouraging responsible citizenship:
Understanding personal responsibility, contributing to the community, and promoting ethical behavior are important aspects of life skills education. 



 

Researcher Laura Greenstein sums up a professional consensus on formative assessment, which is rooted in three significant concepts:

Formative assessment is focused on students.
Formative assessment is instructionally informative.
Formative assessment is based on outcomes. Frequent opportunities for teachers to identify student progress and provide feedback are at the heart of formative assessment. Formative assessments are used to capture snapshots of students' knowledge or skill at particular moments. There are many ways that teachers generate these snapshots of how their students are doing to track their progress.

Some aspects of effective formative assessment strategies include:

Use questions as assessments and as feedback that moves learning forward.
Involve students in thinking about their learning.
Plan to assess learning during and between lessons (short-cycle formative assessment).
Provide immediate feedback.
Look for patterns in student work and plan future instruction based on the results.

1. Consider how AI technology might compel you to revise your course assignments, quizzes, and tests to avoid encouraging unethical or dishonest use of generative AI.  2. Develop and integrate a generative AI policy throughout the course resources:  



Provide clear definitions, expectations, and repercussions of what will happen if students violate the policy.  
Explain the standards of academic integrity in the course, especially as related to use of AI technologies, and review the Integrity of Scholarship and Grades Policy.  






Be clear about what types of AI are acceptable and what versions of the technology students can use or not use.  
Put this policy into D2L and any assignment instructions consistently.  



3. Discuss these expectations when talking about course policies at the beginning of the course and remind students about them as you discuss course assignments:  



Take time to explain to students the pros and cons of generative AI technologies relative to your course. 
Explain the development of your policy and make clear the values, ethics, and philosophies underpinning its development.  






Explain the repercussions of not following the course policy and submit an Academic Dishonesty Report if needed.  



4. If you want to integrate AI in the classroom as an allowed or required resource:  



Consult with MSU IT guidance about recommendations for use and adoption of generative AI technology, including guidelines for keeping you and your data safe.  
Determine if MSU already has access to the tools you desire for free, and if not available through MSU, consider the cost and availability of the resources you will allow or require, and go through MSU's procurement process.   
If you want to require students to use an AI technology that comes with a cost, put the resource into the scheduling system as you would a textbook, so students know that is an anticipated cost to them.  

common myths
for Advanced
AI:A captivating conversation is taking place about the future of artificial intelligence and what it will/should mean for humanity. There are fascinating controversies where the world’s leading experts disagree, such as AI’s future impact on the job market; if/when human-level AI will be developed; whether this will lead to an intelligence explosion; and whether this is something we should welcome or fear. But there are also many examples of boring pseudo-controversies caused by people misunderstanding and talking past each other. 

TIMELINE MYTHS



The first myth regards the timeline: how long will it take until machines greatly supersede human-level intelligence? A common misconception is that we know the answer with great certainty.
One popular myth is that we know we’ll get superhuman AI this century. In fact, history is full of technological over-hyping. Where are those fusion power plants and flying cars we were promised we’d have by now? AI has also been repeatedly over-hyped in the past, even by some of the founders of the field. For example, John McCarthy (who coined the term “artificial intelligence”), Marvin Minsky, Nathaniel Rochester, and Claude Shannon wrote this overly optimistic forecast about what could be accomplished during two months with stone-age computers: “We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College […] An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”

CONTROVERSY MYTHS



Another common misconception is that the only people harboring concerns about AI and advocating AI safety research are Luddites who don’t know much about AI. When Stuart Russell, author of the standard AI textbook, mentioned this during his Puerto Rico talk, the audience laughed loudly. A related misconception is that supporting AI safety research is hugely controversial. In fact, to support a modest investment in AI safety research, people don’t need to be convinced that risks are high, merely non-negligible — just as a modest investment in home insurance is justified by a non-negligible probability of the home burning down.

Natural language processing (NLP) refers to the branch of computer science—and more specifically, the branch of artificial intelligence or AI—concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.
NLP combines computational linguistics—rule-based modeling of human language—with statistical, machine learning, and deep learning models. Together, these technologies enable computers to process human language in the form of text or voice data and to ‘understand’ its full meaning, complete with the speaker or writer’s intent and sentiment. https://byjus.com/biology/flower/ 
NLP drives computer programs that translate text from one language to another, respond to spoken commands, and summarize large volumes of text rapidly—even in real time. There’s a good chance you’ve interacted with NLP in the form of voice-operated GPS systems, digital assistants, speech-to-text dictation software, customer service chatbots, and other consumer conveniences. But NLP also plays a growing role in enterprise solutions that help streamline business operations, increase employee productivity, and simplify mission-critical business processehttps://byjus.com/biology/flower/ 

Department of Haematology
Notes

Full blood counts are performed on automated equipment and provide haemoglobin concentration, red cell indices, white cell count (with a differential count) and platelet count.
The presence of abnormal white cell and red cell morphology is flagged by the analysers.
Blood films may be inspected to confirm and interpret abnormalities identified by the cell counter, or to look for certain specific haematological abnormalities.
Grossly abnormal FBC results and abnormal blood films will be phoned through to the requestor.
There is no need to request a blood film to obtain a differential white count. It is, however, important that clinical details are provided to allow the laboratory to decide whether a blood film, in addition to the automated analysis, is required.
Under some circumstances a differential is not routinely performed, e.g. pre-op, post-op, antenatal and postnatal requests.
Full Blood Counts are performed at CGH and GRH
See also: Reticulocyte Count

The FBC comprises the following tests
Standard

Haemoglobin (Hb)
White Blood Count (WBC)
Platelet Count (Plt)
Red Cell Count (RBC)
Haematocrit (HCT)
Mean Cell Volume - Red cell (MCV)
Mean Cell Haemoglobin (MCH)

Differential White Cell Count (where applicable)

Neutrophils
Lymphocytes
Monocytes
Eosinophils
Basophils

And if appropriate

Blood Film

Sample Requirements
2ml or 4ml EDTA sample or a Paediatric 1ml EDTA sample.

 

Sample Storage and Retention

Pre analysis storage: do not store, send to laboratory within 4 hours.
Sample retention by lab: EDTA samples are retained for a minimum of 48 hours at 2-10°C
Transport of samples may affect sample viability, i.e. FBC results will degenerate if exposed to high temperatures, such as prolonged transportation in a hot car in summer.

This test can be added on to a previous request as long as there is sufficient sample remaining and the sample is less than 24 hours old.
Turnaround Times

Clinical emergency: 30 mins
Other urgent sample: 60 mins
Routine: within 2 hours

Reference Ranges


If references ranges are required for paediatric patients please contact the laboratory for these.

Parameter Patient Reference Range Units Haemoglobin Adult Male 130 - 180 g/L   Adult Female 115 - 165 g/L Red Cell Count Adult Male 4.50 - 6.50 x10^12/L   Adult Female 3.80 - 5.80 x10^12/L Haematocrit Adult Male 0.40 - 0.54 L/L   Adult Female 0.37 - 0.47 L/L Mean Cell Volume Adult 80 - 100 fL Mean Cell Haemoglobin Adult 27 - 32 pg White Cell Count Adult 3.6 - 11.0 x10^9/L Neutrophils Adult 1.8 - 7.5 x10^9/L Lymphocytes Adult 1.0 - 4.0 x10^9/L Monocytes Adult 0.2 - 0.8 x10^9/L Eosinophils Adult 0.1 - 0.4 x10^9/L Basophils Adult 0.02 - 0.10 x10^9/L Platelet Count Adult 140 - 400 x10^9/L


 




 

Department of Haematology
Notes

Full blood counts are performed on automated equipment and provide haemoglobin concentration, red cell indices, white cell count (with a differential count) and platelet count.
The presence of abnormal white cell and red cell morphology is flagged by the analysers.
Blood films may be inspected to confirm and interpret abnormalities identified by the cell counter, or to look for certain specific haematological abnormalities.
Grossly abnormal FBC results and abnormal blood films will be phoned through to the requestor.
There is no need to request a blood film to obtain a differential white count. It is, however, important that clinical details are provided to allow the laboratory to decide whether a blood film, in addition to the automated analysis, is required.
Under some circumstances a differential is not routinely performed, e.g. pre-op, post-op, antenatal and postnatal requests.
Full Blood Counts are performed at CGH and GRH
See also: Reticulocyte Count

The FBC comprises the following tests
Standard

Haemoglobin (Hb)
White Blood Count (WBC)
Platelet Count (Plt)
Red Cell Count (RBC)
Haematocrit (HCT)
Mean Cell Volume - Red cell (MCV)
Mean Cell Haemoglobin (MCH)

Differential White Cell Count (where applicable)

Neutrophils
Lymphocytes
Monocytes
Eosinophils
Basophils

And if appropriate

Blood Film

Sample Requirements
2ml or 4ml EDTA sample or a Paediatric 1ml EDTA sample.

 

Sample Storage and Retention

Pre analysis storage: do not store, send to laboratory within 4 hours.
Sample retention by lab: EDTA samples are retained for a minimum of 48 hours at 2-10°C
Transport of samples may affect sample viability, i.e. FBC results will degenerate if exposed to high temperatures, such as prolonged transportation in a hot car in summer.

This test can be added on to a previous request as long as there is sufficient sample remaining and the sample is less than 24 hours old.
Turnaround Times

Clinical emergency: 30 mins
Other urgent sample: 60 mins
Routine: within 2 hours

Reference Ranges


If references ranges are required for paediatric patients please contact the laboratory for these.

Parameter Patient Reference Range Units Haemoglobin Adult Male 130 - 180 g/L   Adult Female 115 - 165 g/L Red Cell Count Adult Male 4.50 - 6.50 x10^12/L   Adult Female 3.80 - 5.80 x10^12/L Haematocrit Adult Male 0.40 - 0.54 L/L   Adult Female 0.37 - 0.47 L/L Mean Cell Volume Adult 80 - 100 fL Mean Cell Haemoglobin Adult 27 - 32 pg White Cell Count Adult 3.6 - 11.0 x10^9/L Neutrophils Adult 1.8 - 7.5 x10^9/L Lymphocytes Adult 1.0 - 4.0 x10^9/L Monocytes Adult 0.2 - 0.8 x10^9/L Eosinophils Adult 0.1 - 0.4 x10^9/L Basophils Adult 0.02 - 0.10 x10^9/L Platelet Count Adult 140 - 400 x10^9/L


 




 

What a syllabus is
A syllabus is a synecdoche for a course of study—a part of the curricular experience that represents the whole. They are often the very first course texts our students encounter and, accordingly, they frame and preface learning in powerful ways. On one hand, they communicate practical and structural details—where and when a course meets, what to read, and how to contact an instructor. But they also express intellectual and discipline-specific expectations. 
As a special genre of educational texts, syllabi have taken various forms and played various roles over many centuries. In the 17th century ‘syllabus’ was synonymous with ‘table’ or ‘index.’ They served as a structural preview for manuscripts or a list of speakers and topics for a lecture series—they were a means of organizing texts, ideas, and experience. Although that core function remains, post-secondary syllabi have expanded significantly in volume and purview over the past forty years.