Lets consider
dy/dt = ky for all k's for now
Now,
Any constant solution to a differential equation is an equilibrium solution.
I am sure you would agree that y=0 is an equilibrium solution of the given equation.
Now the above equation (as stated by me above), has another solution,
y = e^(kt) ... (1)
So any **system** that adheres to this equation(1) satisfies the differential equation.
Now if a system has the k factor such that k<0
then as t->oo, y -> 0
So this system will follow the equilibrium solution after some period of time. Such systems are called stable systems.
Now if a system has the k factor such that k>0
then as t->oo, y->oo
So this system is unbounded and becomes completely unstable after some period of time.
I am sorry to have introduced the word system, which may be completely alien to you right now. You can think of a system as a machine that takes input and gives certain output and the equation y=e^(kt) as a characteristic equation that describes how much residual noise inputs exist internally in the machine.
Now if i give an input to this machine and if the machine has some residual noise inputs, then it will give me incorrect output.
i.e let's say the machine is supposed to calculate the square of a number. if i give input x to machine then it should ideally give me x^2 but if it has some residual noise, then it will give me (x+some_error)^2
Now you can see how stability and unstability can be realized here. If the above squaring system has the k factor < 0 , then as time progresses the error factor will tend to zero and the machine would give proper output. Thus this system will become stable.
However if it has k factor > 0, then as time progresses, the error factor will tend to infinity and at some point the output will not have any relation to input you give. Thus this system becomes unstable.
I hope this clears some of your doubts if not all.
-- AI