Skills Audit for Maths and Stats - Biomedical Science (BIS114)

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Will Morgan

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From users who are members of Skills Audits for Maths and Stats :

Will Morgan

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Ready to use

9 months ago

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Will Morgan 9 months ago

Gave some feedback: Ready to use

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Will Morgan 10 months, 4 weeks ago

Published this.

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Will Morgan 10 months, 4 weeks ago

Gave some feedback: Needs to be tested

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Will Morgan 10 months, 4 weeks ago

Created this as a copy of BIS110 - Biological Sciences, Zoology draft Skills Audit.

Name	Status	Author	Last Modified
BIS123 - Biochemistry, Biological Sciences draft Skills Audit	Needs to be tested	Will Morgan	23/07/2024 14:34
BIS110 - Biological Sciences, Zoology draft Skills Audit	Needs to be tested	Will Morgan	23/07/2024 14:34
Skills Audit for Maths and Stats - Biomedical Science (BIS114)	Ready to use	Will Morgan	23/07/2024 14:31

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Question groups

Group 45 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

Using prefixes (milli) in this case.
5.
Ready to use

Using prefixes - milli and micro.
6.
Ready to use

Multiples, factors, lowest common multiples and highest common factors.
7.
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.
8.
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.
9.
Ready to use

Applying the order of operators.
10.
Ready to use

Round numbers to a given number of decimal places.
11.
Ready to use

Round numbers to a given number of significant figures.
12.
Ready to use

Round numbers to a given number of significant figures.
13.
Ready to use

State the Upper and lower bound of a distance that has been rounded to either the nearest 10 or 100 miles.
14.
Ready to use

Calculate the percentage increase (as a percentage) given a number and the size of the increase.
15.
Ready to use

Given a student discount, calculate a discounted price.
16.
Ready to use

Compound percentage change.
17.
Ready to use

Find the original price before a discount by dividing the new price by the percentage discount.
18.
Ready to use

Find a percentage of an amount.
19.
Ready to use

Calculate one number as percentage of another.
20.
Ready to use

Given the number of international students enrolled on a course of $n$ students, calculate the percentage of 'home' students.
21.
Ready to use

Dividing amounts in ratios
22.
Ready to use

Convert numbers greater than 1 into standard form/scientific notation.
23.
Ready to use

Convert numbers between 0 and 1 intro standard form/scientific notation.
24.
Ready to use

Using indices rules to rewrite an expression from $a^\frac{m}{n}$ to $b$ , for integers $a$ , $b$ , $m$ and $n$ .
25.
Ready to use

perform a calculation involving negative indices.
26.
Ready to use

Simple exercise in collecting terms in different powers of $x$
27.
Ready to use

Simple exercise in collecting terms in different powers of $x$
28.
Ready to use

This question is made up of 10 exercises to practice the multiplication of brackets by a single term.
29.
Ready to use

Factorise an expression of 2 or 3 terms where the gcd is a letter times a number. Part of HELM Book 1.3.4
30.
Ready to use

Expanding two linear brackets multiplied together.
31.
Ready to use

Expand two brackets involving powers of $x$ .
32.
Ready to use

Solve linear equations with unkowns on both sides. Including brackets and fractions.
33.
Ready to use

Substitute values into an algebraic expression and calculate the result.
34.
Ready to use

Solving a pair of linear simultaneous equations, giving answers as integers or fractions.
35.
Ready to use

Rearrange a specific formula. No randomisation.
36.
Ready to use

Calculations involving Standard form.

37.

Ready to use

Draws a triangle based on 3 side lengths and randomises asking for hypotenuse or not.

Variable	Value	Description
statement2
sh2_gen

38.

Ready to use

Finding the area of a circle when given the diameter of the circle.

Variable	Value	Description
d

39.
Ready to use

Calculate the volume of different 3D shapes, given the units and measurements required. The formulae for the volume of each shape are available as steps if required.
40.
Ready to use

Calculate the volume of different 3D shapes, given the units and measurements required. The formulae for the volume of each shape are available as steps if required.
41.
Ready to use

Calculating gradient and finding intercept from a geogebra graph.
42.
Ready to use

This question provides a list of data to the student. They are asked to find the "range".
43.
Ready to use

Calculating the Mean from a basic list of integers.
44.
Ready to use

This question provides a list of data to the student. They are asked to find the "mode".
45.
Ready to use

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

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 - Biomedical Science (BIS114)

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Taxonomy: mathcentre

Taxonomy: Kind of activity

Taxonomy: Context

Contributors

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Checkpoint description

Will Morgan 9 months ago

Will Morgan 10 months, 4 weeks ago

Will Morgan 10 months, 4 weeks ago

Will Morgan 10 months, 4 weeks ago

Question groups

Topics

Learning objectives

Base diagnostic algorithm

Custom diagnostic algorithm

On leaving a question

On timeout

5 minutes before timeout