Skills Audit for Maths and Stats - Nursing (SNM148)

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Will Morgan

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Will Morgan

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Ready to use

9 months, 1 week ago

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Will Morgan 9 months, 1 week ago

Gave some feedback: Ready to use

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Will Morgan 10 months, 3 weeks ago

Gave some feedback: Needs to be tested

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Will Morgan 10 months, 3 weeks ago

Published this.

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Will Morgan 10 months, 3 weeks ago

Created this.

There is only one version of this exam that you have access to.

Question groups

Group 53 questions

1.
Ready to use

Whole number division in a context of number of tablets per day based on a tablet size and a daily prescribed amount.
2.
Ready to use

Division resulting in decimals in the context of a dose per hour.
3.
Ready to use

Simple unit conversion with metric units.
4.
Ready to use

Metric Unit conversion - division by 1000.
5.
Ready to use

Using prefixes (milli) in this case.
6.
Ready to use

Using prefixes - milli and micro.
7.
Ready to use

convert from micrograms to milligrams.
8.
Ready to use

convert from inches to cm.
9.
Ready to use

Number sequences - find a missing number
10.
Ready to use

Questions testing understanding of the precedence of operators using BIDMAS, applied to integers. These questions only test DMAS. That is, only Division/Multiplcation and Addition/Subtraction.
11.
Ready to use

Questions testing understanding of the precedence of operators using BIDMAS, applied to integers. These questions only test DMAS. That is, only Division/Multiplcation and Addition/Subtraction.
12.
Ready to use

Applying the order of operators.
13.
Ready to use

Round numbers to a given number of decimal places.
14.
Ready to use

Round numbers to a given number of significant figures.
15.
Ready to use

State the Upper and lower bound of a distance that has been rounded to either the nearest 10 or 100 miles.
16.
Ready to use

Calculations with negative numbers.
17.
Ready to use

Calculations with negative numbers.
18.
Ready to use

Calculations with negative numbers.
19.
Ready to use

Calculations with negative numbers.
20.
Ready to use

Calculate the percentage increase (as a percentage) given a number and the size of the increase.
21.
Ready to use

Given a student discount, calculate a discounted price.
22.
Ready to use

Compound percentage change.
23.
Ready to use

Find the original price before a discount by dividing the new price by the percentage discount.
24.
Ready to use

Find a percentage of an amount.
25.
Ready to use

Calculate one number as percentage of another.
26.
Ready to use

Given the number of international students enrolled on a course of $n$ students, calculate the percentage of 'home' students.
27.
Ready to use

Calculating the LCM and HCF of numbers by using prime factorisation.
28.
Ready to use

This question tests the student's ability to identify equivalent fractions through spotting a fraction which is not equivalent amongst a list of otherwise equivalent fractions. It also tests the students ability to convert mixed numbers into their equivalent improper fractions. It then does the reverse and tests their ability to convert an improper fraction into an equivalent mixed number.
29.
Ready to use

Manipulate fractions in order to add and subtract them. The difficulty escalates through the inclusion of a whole integer and a decimal, which both need to be converted into a fraction before the addition/subtraction can take place.
30.
Ready to use

Manipulate fractions in order to add and subtract them. The difficulty escalates through the inclusion of a whole integer and a decimal, which both need to be converted into a fraction before the addition/subtraction can take place.
31.
Ready to use

Several problems involving dividing fractions, with increasingly difficult examples, including mixed numbers and complex fractions.
32.
Ready to use

Several problems involving the multiplication of fractions, with increasingly difficult examples, including a mixed fraction and a squared fraction. The final part is a word problem.
33.
Ready to use

This question tests the student's ability to identify equivalent fractions through spotting a fraction which is not equivalent amongst a list of otherwise equivalent fractions. It also tests the students ability to convert mixed numbers into their equivalent improper fractions. It then does the reverse and tests their ability to convert an improper fraction into an equivalent mixed number.
34.
Ready to use

Put fractions in size order.
35.
Ready to use

Convert a percentage to a fraction.
36.
Ready to use

Convert a decimal to a fraction.
37.
Ready to use

Convert a fraction into a decimal.
38.
Ready to use

Proportional calculation in context.
39.
Ready to use

Picking a ratio out of a list that is not equivalent to the others.
40.
Ready to use

Dividing amounts in ratios
41.
Ready to use

Decide whether each of the described sets of data is drawn from a discrete or continuous distribution.
42.
Ready to use

This question is about identifying what types of charts or visual representations of data you can use for different data sets.
43.
Ready to use

This question is about correctly interpreting pie charts.
44.
Ready to use

Reading a value from a simple bar chart.
45.
Ready to use

This question provides a list of data to the student. They are asked to find the "range".
46.
Ready to use

Calculating the Mean from a basic list of integers.
47.
Ready to use

This question provides a list of data to the student. They are asked to find the "mode".
48.
Ready to use

This question provides a list of data to the student. They are asked to find the "median".
49.
Ready to use

Identifying measures of spread or location (average)
50.
Ready to use

Calculate an intersection probability given a two way table.
51.
Ready to use

Tests understanding of scatter plots and related concepts.
52.
Ready to use

Calculate probability of selecting coloured counters from a bag.
53.
Ready to use

Predicting the probability of an unbiased coin landing on heads based on the results of previous throws.

Topics

No topics have been defined.

Diagnostic algorithm

Extend built-in algorithm?

Base diagnostic algorithm

state (Produces the initial value of the state object): // should be renamed "initial_state"
    [
        "topics": map(
            [
                "topic": topic,
                "status": "unknown" // "unknown", "passed", or "failed"
            ],
            topic,
            values(topics)
        ),
        "retries": 3,
        "finished": false,
    ]

topics_by_objective (A dictionary mapping a learning objective name to a list of indices of topics):
    dict(map(
        let(
            ltopics, values(topics),
            indices, filter(lo["name"] in ltopics[j]["learning_objectives"], j, 0..len(ltopics)-1),
            [lo["name"],indices]
        ),
        lo,
        learning_objectives
    ))

unknown_topics (Which topics are still unknown?): 
    map(x["topic"],x,filter(x["status"]="unknown",x,state["topics"]))

first_topic (The first topic to pick a question on):
    unknown_topics[floor(len(unknown_topics)/2)]["name"]

first_question (The first question to show the student):
    random(topics[first_topic]["questions"])

get_dependents (An expression which gets the topics to update after answering a question):
    expression("""
        [target] + flatten(map(eval(get_dependents,["target":t,"correct":correct]),t,topics[target][if(correct,"depends_on","leads_to")]))
    """)

correct (Did the student get the current question right?):
    current_question["credit"]=1

after_answering (Update the state after the student answers a question):
    let(
        ntopics, eval(get_dependents,["target":current_topic,"correct":correct])
    ,   nstate, state + ['topics': map(
                    if(tstate["topic"]["name"] in ntopics, tstate + ["status":if(correct,"passed","failed")], tstate),
                    tstate,
                    state["topics"]
                )]
    , nstate
    )

action_retry (Use up one retry and visit the same topic again):
    [
        "label": translate("diagnostic.use retry"),
        "state": state + ["retries": state["retries"]-1],
        "next_question": random(topics[current_topic]["questions"])
    ]

action_stop (Stop the exam):
    [
        "label": translate("diagnostic.end test"),
        "state": state,
        "next_question": nothing
    ]

action_move_on (Move to the next topic, or end the exam if there are no more):
    let(
        state, after_answering,
        immediate_next_topics, topics[current_topic][if(correct, "leads_to", "depends_on")],
        unknown_topics, map(x["topic"],x,filter(x["status"]="unknown",x,state["topics"])),
        unknown_immediate_topics, filter(x["name"] in immediate_next_topics,x,unknown_topics),
        next_topics, if(len(unknown_immediate_topics), unknown_immediate_topics, unknown_topics),
        finished, len(next_topics)=0 or state["finished"],
        topic,
            if(not finished,
                next_topics[floor(len(next_topics)/2)]["name"]
            ,
                nothing
            ),
        [
            "label": translate("diagnostic.move to next topic"),
            "state": after_answering,
            "next_question": if(not finished, random(topics[topic]["questions"]), nothing)
        ]
    )

can_move_on:
    action_move_on["next_question"]<>nothing

next_actions (Actions to offer to the student when they ask to move on):
    let(
        feedback, retries_feedback+"\n\n"+translate("diagnostic.next step question")
    ,   [
            "feedback": feedback,
            "actions": if(not correct and state["retries"]>0, [action_retry], []) + if(can_move_on,[action_move_on],[action_stop])
        ]
    )

after_exam_ended (Update the state after the exam ends):
    let(
        state, after_answering,
        ntopics, map(t+["status": if(t["status"]="unknown","failed",t["status"])],t,state["topics"]),
        state+["finished": true]
    )

finished (Is the test finished? True if there are no unknown topics):
    len(unknown_topics)=0 or state["finished"]

total_progress:
    let(
        num_topics, len(state["topics"]),
        known, filter(tstate["status"]<>"unknown",tstate,state["topics"]),
        passed, filter(tstate["status"]="passed",tstate,known),
        num_known, len(known),
        num_passed, len(passed),
        [
            "name": translate("control.total"),
            "progress": if(num_topics>0,num_known/num_topics,0), 
            "credit": if(num_known>0,num_passed/num_topics,0)
        ]
    )

learning_objective_progress:
    map(
        let(
            tstates, map(state["topics"][j],j,topics_by_objective[lo["name"]]),
            known, filter(tstate["status"]<>"unknown",tstate,tstates),
            passed, filter(tstate["status"]="passed",tstate,known),
            num_topics, len(tstates),
            num_known, len(known),
            num_passed, len(passed),
            ["name": lo["name"], "progress": if(num_topics>0,num_known/num_topics,0), "credit": if(finished,num_passed/num_topics,if(num_known>0,num_passed/num_known,0))]
        ),
        lo,
        learning_objectives
    )

progress (Progress on each of the learning objectives, plus total progress):
    learning_objective_progress+
    total_progress

retries_feedback:
    translate("diagnostic.now assessing topic", ["current_topic": current_topic]) + " " +
    let(
        retries, state["retries"], 
        pluralise(retries, translate("diagnostic.one retry left"), translate("diagnostic.retries left", ["retries": retries ]))
    )
    + " " +
    let(
        p,total_progress["progress"],
        percentage, dpformat(100p, 0),
        translate("diagnostic.percentage completed", ["percentage": percentage])
    )

weak_objective_threshold (The amount of credit below which a learning objective is considered weak):
    0.6

finished_feedback:
    let(
        weak_objectives, filter(p["credit"]<weak_objective_threshold, p, learning_objective_progress),
    //
        translate("diagnostic.test is over") + " "
        +
        if(len(weak_objectives)=0,
            translate("diagnostic.passed all lo")
        ,
            translate("diagnostic.more work on lo", ["los": 
                join(map(lo["name"], lo, weak_objectives),", ")])
        )
    )

feedback:
    if(finished,
        finished_feedback,
        retries_feedback
    )

Custom diagnostic algorithm

Interface theme

Upload a new theme

Interface language

Allow students to print question content?

Show student's name?

Enter review mode immediately on ending the exam?

	Always	In submitted mode	Only in review mode	Never
Show answer correctness
Show the student's score
Show the maximum score
Show part feedback messages
Show expected answers
Show question advice

Pass threshold

Feedback messages

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Skills Audit for Maths and Stats - Nursing (SNM148)

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Taxonomy: mathcentre

Taxonomy: Kind of activity

Taxonomy: Context

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Checkpoint description

Will Morgan 9 months, 1 week ago

Will Morgan 10 months, 3 weeks ago

Will Morgan 10 months, 3 weeks ago

Will Morgan 10 months, 3 weeks ago

Question groups

Topics

Learning objectives

Base diagnostic algorithm

Custom diagnostic algorithm

On leaving a question

On timeout

5 minutes before timeout