Shows how to mark a boolean expression, by checking all possible values of the free variables. There's an information step containing a reminder of the syntax for boolean operations.

Identify the truth value of an inequality (T/F) between two numbers

Evaluating a linear function for a given value of $x$.

Substitute values into an algebraic expression and calculate the result.

Given $f(x)=(x+b)^n$. Find the gradient and equation of the chord between $(a,f(a))$ and $(a+h,f(a+h))$ for randomised values of $a$, $b$ and $h$.

This question assesses the learner's ability of calculating confidence intervals for numerical data and conducting a one-sample t-test.

Randomized input values: sample summary statistics and confidence level.

Adapted from question 7.12 in OpenIntro Statistics (4th ed).

Part (a) - dividing a total quantity given a ratio

Part (b) - given the value of one part of the ratio to find the total quantity.

Rounding three different values to different significant figures.

Substitute values into formulae for the area or volume of various geometric objects.

Here you need to choose which formula you would use to find the red dashed value from the solid green values.  The view is three-dimensional and you can rotate it to get a better view.

Variable defintions in the formulas:
$\theta$ is an angle
Adj. is the length of the side adjacent to the known angle
Opp. is the length of the side opposite the known angle
Hyp. is the length of the hypotenuse


Your goal is to get twenty correct answers quickly. Incorrect answers show a highlight of the correct answer to select to continue.  The timer starts as soon as you choose your first answer and continues until you get 20 correct.  Select save answer after your results show in the applet.

Calculate the heat losses from a model building based on the U values, dimensions and other parameters specified. In addition calculate the annual running costs and payback period for improvements to the building Fabric.

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This questions assesses the ability to conduct an ANOVA and interpret the results.

Adaptive marking: an error in calculating F can be carried over to the calculation of the p-value as well as the test conclusion.

In the first part, the student is asked to enter dimensions of a box in a spreadsheet.

The values are extracted as a list of numbers by changing the interpreted_answer note in the first part's marking algorithm, and the calculated volume is used as the answer to the second part, through adaptive marking.

Using basic derivatives to calculate the gradient function of a hill $y=-e^x+b\ln\left(x\right)+c$, and then substituting values to find the gradient at specific distance from the sea. 

This question plots a general amplitude modulated carrier signal defined by $v_s(t) = (V_{DC} + V_m \cos(2\pi f_m t))\cos(2\pi f_c t)$, where $V_{DC}$ is a DC offset, $V_m$ is the message amplitude, $f_m$ is the message frequency and $f_c$ is the carrier frequency ($f_c = 20f_m$ in this question). The student must identify the values of $V_{DC}$ and $V_m$ and enter these values into the appropriate gaps in the equation of the AM signal.

Student needs to solve a quadratic equation to calculate time taken for a diver to hit the water after diving from a diving board. Height of the board and initial upward velocity of the diver are randomly generated values. student needs to know that surface of the water is height 0, and only positive root of quadratic has physical meaning. Question is set to always give one positieve and one negative root.

$A,\;B$ $2 \times 2$ matrices. Find eigenvalues and eigenvectors of both. Hence or otherwise, find $B^n$ for largish $n$.

Given a 3 x 3 matrix, and two eigenvectors find their corresponding eigenvalues. Also fnd the characteristic polynomial and using this find the third eigenvalue and a normalised eigenvector $(x=1)$.

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Example of an explore mode question. Student is given a 3x3 matrix and is asked to find the characteristic polynomial and eigenvalues, and then eigenvectors for each eigenvalue. The part asking for eigenvectors can be repeated as often as the student wants, to be used for different eigenvalues.

Assessed: calculating characteristic polynomial and eigenvectors.

Feature: any correct eigenvalue will be recognised by the marking algorithm, even multiples of the obvious one(s) (which can be read off from the reduced row echelon form)

Randomisation: Not randomised, just using particular matrices. I am still working on how to randomise this for 3x3; a randomised 2x2 version exists. I have several different versions for 3x3 (not all published yet), so I could make a random choice between these in a test.

The implementation uses linear algebra functions such as "find reduced echelon form" or "find kernel of a reduced echelon form", from the extension "linalg2".

This is a copy of a question from the Numbas demos project, with references to the editor removed.

The student is shown a plot of a mystery function. They can enter values of $x$ check, within the bounds of the plot.

They're asked to give the formula for the function, and then asked for its value at a very large value of $x$.

A plot of the student's function updates automatically as they type. Adaptive marking is used for the final part to award credit if the student gives the right value for their incorrect function.

Compute a table of values for a quadratic function. A JSXgraph (the graph paper) plot shows the curve going through the entered values.

Compute a table of values for a quadratic function. A JSXgraph (the graph paper) plot shows the curve going through the entered values. The student input is now disconnected from the graph so that they slide the points usually after they input the values and the answer fields are not updated.